JP2023052052A - Crispr effector system based diagnostics for virus detection - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide nucleic acid detection technologies that provide high specificity and sensitivity at low-cost and are of great utility in both clinical and basic research settings.

SOLUTION: Provided herein is a nucleic acid detection system comprising: a CRISPR system comprising an effector protein and one or more guide RNAs designed to bind to corresponding target molecules; an RNA-based masking construct; and optionally, nucleic acid amplification reagents to amplify target RNA molecules in a sample. In another aspect, the embodiments provide a polypeptide detection system comprising: a CRISPR system comprising an effector protein and one or more guide RNAs designed to bind a trigger RNA; an RNA-based masking construct; and one or more detection aptamers comprising a masked RNA polymerase promoter binding site or a masked primer binding site. In some embodiments, the system may be used to detect viruses in samples.

SELECTED DRAWING: None

COPYRIGHT: (C)2023,JPO&INPIT

Description

Cross-Reference to Related Applications No., U.S. Provisional Application No. 62/530,086 filed July 7, 2017, U.S. Provisional Application No. 62/568,315 filed October 5, 2017, November 2017 No. 62/588,138, filed Dec. 17, and U.S. Provisional Application No. 62/596,735, filed Dec. 8, 2017. The entire contents of the applications identified above are fully incorporated herein by reference.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

This invention was made with United States Government support under Grant Nos. MH100706, MH110049, AI110818 from the National Institutes of Health and Grant No. HDTRA1-14-1-0006 from the Defense Threat Reduction Agency. The United States Government has certain rights in this invention.
[Technical field]

The subject matter disclosed herein is generally directed to rapid diagnostics related to the use of clustered regularly interspaced short palindromic repeats (CRISPR) effector systems.

Nucleic acids are a ubiquitous feature of biological information. The ability to rapidly detect nucleic acids with high sensitivity and single-base specificity using portable instruments will revolutionize the diagnosis and surveillance of many diseases, provide valuable epidemiological information, and contribute to the advancement of universal science. It has the potential to function as a public tool. A number of methods have been developed to detect nucleic acids (Du et al., 2017; Green et al., 2014; Kumar et al., 2014; Pardee et al., 2014; Pardee et al., 2016; Urdea et al. ., 2006) are subject to compromises between sensitivity, specificity, simplicity, and speed. For example, quantitative PCR methods are sensitive but expensive and rely on complex equipment. As such, its use is limited to highly trained operators in a laboratory environment. Other methods, such as novel methods that combine isothermal nucleic acid amplification with portable equipment (Du et al., 2017; Pardee et al., 2016), offer high detection specificity in the point-of-care (POC) setting. However, its use is somewhat limited due to its low sensitivity. Nucleic acid diagnostics are becoming increasingly suitable for a variety of health care applications, and detection techniques that provide high specificity and sensitivity at low cost would be of great value in clinical and basic research settings.

In one aspect, the invention provides a CRISPR system comprising an effector protein and one or more guide RNAs designed to bind to the corresponding target molecule, an RNA-based masking construct, and optionally a target RNA in a sample. A nucleic acid detection system is provided that includes nucleic acid amplification reagents for amplifying molecules. In other aspects, some embodiments are CRISPR systems comprising one or more guide RNAs designed to bind to effector proteins and trigger RNAs, RNA-based masking constructs, and masked RNA polymerase promoter binding sites Alternatively, a polypeptide detection system comprising one or more detection aptamers containing masked primer binding sites is provided.

Additionally, in some embodiments, the system may further comprise nucleic acid amplification reagents. These nucleic acid amplification reagents may contain primers containing RNA polymerase promoters. In certain embodiments, sample nucleic acid may be amplified to provide a DNA template containing an RNA polymerase promoter, which by transcription produces a target RNA molecule. The nucleic acid may be DNA and may be amplified by any method described herein. Said nucleic acid may be RNA and may have been amplified by the reverse transcription method described herein. The aptamer sequence may be amplified upon unmasking the primer binding site, which transcribes the trigger RNA from the amplified DNA product. Said target molecule may be target DNA, and said system may further comprise a primer that binds to target DNA, and an RNA polymerase promoter.

In one exemplary embodiment, the CRISPR system effector protein is an RNA target effector protein. RNA target effector proteins include, for example, C2c2 (now known as Casl3a), Casl3b, and Casl3a. Obviously, the term "C2c2" herein is interchangeable with "Casl3a". In another exemplary embodiment, the RNA target effector protein is C2c2. In other embodiments, the C2c2 effector protein is Leptotrichia, Listeria, Corynebacter, Satterella, Legionella, Treponema, Filifactor, Eubacterium, Streptococcus, Lactobacillus, Mycoplasma, Bacteroides, Flaviibora, Flavobacterium, Sphaerocheta, Azospirillum, Gluco It is from an organism selected from the group consisting of the genera Nacetobacter, Neisseria, Rosebria, Parvivacrum, Staphylococcus, Nitratifructor, Mycoplasma, Campylobacter, and Lachnospira. Alternatively, the C2c2 effector protein is selected from the group consisting of Leptotrichia shaii, Leptotrichia weedii, Listeria seeligeri, Clostridium aminophyllum, Canobacterium gallinarum, Pardibacter propionisigenes, Listeria weihenstephanensis. It is a living organism. Alternatively, the C2c2 effector protein is L. Weedy F0279 or L.I. Weidi F0279 (Lw2) is a C2C2 effector protein. In other aspects, the one or more guide RNAs are designed to detect single nucleotide polymorphisms, transcript splicing variants, or frameshift mutations in the target RNA or DNA.

In other embodiments, the one or more guide RNAs are designed to bind to one or more target molecules used for diagnosis of disease states. In further embodiments, the disease state is an infection, organ disease, blood disease, immune system disease, cancer, brain and nervous system disease, endocrine disease, pregnancy or childbirth related disease, genetic disease, or environmental disease. be. In further embodiments, the disease state is cancer, an autoimmune disease, or an infection.

In further embodiments, said one or more guide RNAs are designed to bind to one or more target molecules comprising cancer-specific somatic mutations. Said cancer-specific mutation may confer drug resistance. This drug resistance mutation may be induced by treatment with ibrutinib, erlotinib, imatinib, gefitinib, crizotinib, trastuzumab, vemurafenib, RAF/MEK, immune checkpoint inhibition therapy, or anti-estrogen therapy. The cancer-specific mutations include programmed death ligand 1 (PD-L1), androgen receptor (AR), Bruton's tyrosine kinase (BTK), epidermal growth factor receptor (EGFR), BCR-Abl, c- kit, PIK3CA, HER2, EML4-ALK, KRAS, ALK, ROS1, AKT1, BRAF, MEK1, MEK2, NRAS, RAC1, and ESR1. good too. The cancer-specific mutations include the following chromosomal bands: 6q16.1-q21, 6q22.31-q24.1, 6q25.1-q26, 7p11.2-q11.1, 8p23.1, 8p11.23- p11.21 (including IDO1 and IDO2), 9p24.2-p23 (including PDL1 and PDL2), 10p15.3, 10p15.1-p13, 11p14.1, 12p13.32-p13.2, 17p13.1 ( ALOX12B, ALOX15B), and CASP8, B2M, PIK3CA, SMC1A, ARID5B, TET2, ALPK2, COL5A1, TP53, DNER, NCOR1, except for chromosomal-wide events affecting any of 22q11.1-q11.21 , MORC4, CIC, IRF6, MYOCD, ANKLE1, CNKSR1, NF1, SOS1, ARID2, CUL4B, DDX3X, FUBP1, TCP11L2, HLA-A, B, or C, CSNK2A1, MET, ASXL1, PD-L1, PD-L2, It may be mutation or copy number increase of a gene selected from the group consisting of IDO1, IDO2, ALOX12B and ALOX15B.

In a further embodiment, said one or more guide RNAs may be designed to bind to one or more target molecules comprising a loss of heterozygosity (LOH) marker.

In further embodiments, the one or more guide RNAs may be designed to bind to one or more target molecules that contain single nucleotide polymorphisms (SNPs). The disease may be heart disease and the target molecule may be VKORC1, CYP2C9 and CYP2C19.

In further embodiments, the disease state may be a pregnancy or childbirth related disease or a genetic disease. Said sample may be a blood sample or a mucus sample. Said diseases include trisomy 13, trisomy 16, trisomy 18, Klinefelter's syndrome (47, XXY), (47, XYY) and (47, XXX), Turner's syndrome, Down's syndrome (trisomy 21 ), cystic fibrosis, Huntington's disease, beta-thalassemia, muscular dystrophy, sickle cell anemia, porphyria, fragile X syndrome, Robertsonian translocations, Angelman syndrome, DiGeorge syndrome, and Wolf-Hirschhorn It may be selected from the group consisting of syndromes.

In further embodiments, said infection is caused by a virus, bacteria, or fungus, or said infection is a viral infection. In certain embodiments, viral infections are caused by double-stranded RNA viruses, positive-stranded RNA viruses, negative-stranded RNA viruses, retroviruses, or combinations thereof. Alternatively, the viral infection may be a coronavirus, picornaviridae, caliciviridae, flaviviridae, togaviridae, bornaviridae, filoviridae, paramyxoviridae, pneumoviridae, It is caused by the genera Rhabdoviridae, Arenaviridae, Bunyaviridae, Orthomyxoviridae, or Deltavirus. Alternatively, the viral infection is coronavirus, SARS, poliovirus, rhinovirus, hepatitis A virus, Norwalk virus, yellow fever virus, West Nile virus, hepatitis C virus, dengue virus, Zika virus, rubella virus, Ross virus. River virus, Sindbis virus, Chikungunya virus, Borna virus, Ebola virus, Marburg virus, Measles virus, Mumps virus, Nipah virus, Hendra virus, Newcastle disease virus, Human respiratory syncytial virus, Rabies virus, Lassa virus, Hanta Caused by viruses, Crimean-Congo hemorrhagic fever virus, influenza, or hepatitis D virus.

In other embodiments of the invention, the RNA-based masking construct suppresses production of a detectable positive signal. Alternatively, the RNA-based masking construct suppresses production of a detectable positive signal by masking the detectable positive signal, or alternatively produces a detectable negative signal. Alternatively, said RNA-based masking construct comprises a silencing RNA that suppresses production of a gene product encoded by the reporting construct, said gene product producing a detectable positive signal upon expression.

In a further embodiment, said RNA-based masking construct is a ribozyme that produces said detectable negative signal, and said detectable positive signal is produced upon inactivation of said ribozyme. Alternatively, the ribozyme converts a substrate to a first color and the substrate changes to a second color when the ribozyme is inactivated.

In another embodiment, said RNA-based masking factor is an RNA aptamer. Alternatively, the aptamer sequesters an enzyme that acts on a substrate to produce a detectable signal upon release from the aptamer. Alternatively, the aptamer sequesters a pair of factors that bind to produce a detectable signal upon release from the aptamer.

In other aspects, the RNA-based masking construct comprises an RNA oligonucleotide to which a detectable ligand and masking moiety are attached. In other embodiments, the detectable ligand is a fluorophore and the masking moiety is a quenching molecule, such as, but not limited to, NASBA (Nucleic Acid Sequence Based Amplification) or RPA reagents. It is an amplifying reagent.

In another aspect, the invention provides a diagnostic device comprising one or more discrete volumes, each of said one or more discrete volumes designed to bind to a CRISPR effector protein, a corresponding target molecule. It also contains one or more guide RNAs, an RNA-based masking construct, and may also contain nucleic acid amplification reagents.

In another aspect, the invention provides a diagnostic device comprising one or more discrete volumes, each discrete volume comprising a CRISPR effector protein, one or more guide RNAs designed to bind to a trigger RNA, a masked One or more detection aptamers containing an RNA polymerase promoter binding site or a masked primer binding site are included, and may further include nucleic acid amplification reagents.

In some embodiments, the discrete volumes are droplets, discrete volumes are defined in a solid substrate, are microwells, or are spots defined in a substrate such as a paper substrate.

In certain other exemplary embodiments, the nucleic acid detection system is designed to detect one or more viral targets and is used in combination with antiviral therapy. In certain exemplary embodiments, said antiviral therapy is a Class 2, Type VI CRISPR-based antiviral system. For example, the nucleic acid detection system may be used in conjunction with an antiviral system against drug resistance or susceptibility of viral strains infecting a particular patient or prevalent in a given outbreak to select appropriate therapeutic agents. good too. This includes diagnostic systems that can detect novel mutations that arise during therapy, as well as mutations known to lead to the development of therapy resistance. Such diagnostic systems of embodiments disclosed herein can be used as a companion diagnostic to antiviral therapy to select appropriate initial antiviral therapy and in response to resistance variants that may arise. Antiviral therapy may be modified. In an exemplary embodiment, wherein the antiviral system is a Class 2, Type VI CRISPR-based antiviral therapy, a Class 2, Type VI CRISPR-based antiviral therapy using the diagnostic system of the embodiments disclosed herein Guide sequences may be selected and/or modified that are used to direct effector proteins to target viral agent nucleic acid sequences.

In one aspect, said RNA target effector protein is a CRISPR, type VI RNA target effector protein such as C2c2, Casl3b, or Casl3c. In certain exemplary embodiments, the C2c2 effector protein is Leptotrichia, Listeria, Corynebacter, Satterella, Legionella, Treponema, Filifactor, Eubacterium, Streptococcus, Lactobacillus, Mycoplasma, Bacteroides, Flaviibora, Flavobacterium, Spherocheta , Azospirillum, Gluconacetobacter, Neisseria, Rosebria, Parvivacrum, Staphylococcus, Nitratifructor, Mycoplasma, and Campylobacter. Alternatively, said C2c2 effector protein is derived from Leptotrichia shaiii, L. selected from the group consisting of Weidii, Listeria seeligeri, Lachnospiraceae, Clostridium aminophyllum, Carnobacterium gallinarum, Pardibacter propionisigenes, Listeria weihenstephanensis, Listeriaceae, and Rhodobacter capsulata be done. Alternatively, said C2c2 effector protein is L. Weedy F0279 or L.I. Weidi F0279 (Lw2) is a C2c2 effector protein. In another aspect, the one or more guide RNAs are designed to bind to one or more target RNA sequences used for diagnosis of disease states.

In certain exemplary embodiments, said RNA-based masking construct suppresses production of a detectable positive signal. Alternatively, the RNA-based masking construct suppresses production of a detectable positive signal by masking a detectable positive signal, or alternatively produces a detectable negative signal. Alternatively, said RNA-based masking construct comprises a silencing RNA that inhibits production of a gene product encoded by a reporting construct, said gene product producing said detectable positive signal upon expression.

In another exemplary embodiment, said RNA-based masking construct is a ribozyme that produces a detectable negative signal, and inactivation of said ribozyme produces said detectable positive signal. In one exemplary embodiment, the ribozyme converts a substrate to a first color, and the substrate changes to a second color when the ribozyme is inactivated. In another exemplary embodiment, said RNA-based masking factor is an aptamer sequestering enzyme, said enzyme producing a detectable signal upon release from said aptamer upon acting on a substrate. Alternatively, the aptamer sequesters a pair of factors that bind to produce a detectable signal upon release from the aptamer.

In another exemplary embodiment, the RNA-based masking construct comprises an RNA oligonucleotide to which a detectable ligand oligonucleotide and a masking component have been added. In certain exemplary embodiments, said detectable ligand is a fluorophore and said masking moiety is a quencher molecule.

In another aspect, the invention provides a method of detecting target RNA in a sample. Said method comprises: distributing a sample or set of samples into one or more discrete volumes comprising an effector protein, a CRISPR system comprising one or more guide RNAs, an RNA-based masking construct; incubating the sample or set of samples under conditions sufficient to allow the guide RNA to bind to one or more target molecules, allowing the one or more guide RNAs to bind to the one or more target molecules. activating said CRISPR effector protein by (wherein activation of said CRISPR effector protein modifies said RNA-based masking construct to produce a detectable positive signal), and said detectable positive detecting a signal, wherein detection of said detectable positive signal indicates the presence of one or more target molecules in said sample.

In another aspect, the invention provides a method of detecting peptides in a sample. The method distributes a sample or set of samples into a set of discrete volumes containing a peptide detection aptamer, an effector protein, a CRISPR system comprising one or more guide RNAs, an RNA-based masking construct, wherein said peptide detection aptamer comprises a masked RNA polymerase site and is configured to bind to one or more target molecules; said peptide detection aptamer may bind to said one or more target molecules; incubating the sample or set of samples under sufficient conditions where binding of the aptamer to the corresponding target molecule exposes the RNA polymerase binding site and causes RNA synthesis of the trigger RNA; activating a CRISPR effector protein by binding of said one or more guide RNAs to said trigger RNA, wherein activation of said CRISPR effector protein modifies said RNA-based masking construct to produce a detectable positive signal is produced), and detecting said detectable positive signal, wherein detection of said detectable positive signal is indicative of the presence of one or more target molecules in the sample. .

In certain exemplary embodiments, such methods further comprise amplifying said sample RNA or said trigger RNA. In other embodiments, amplifying RNA comprises amplification by NASBA or RPA.

In certain exemplary embodiments, said CRISPR effector protein is a CRISPR, type VI RNA target effector protein such as C2c2 or Casl3b. In another exemplary embodiment, the C2c2 effector protein is Leptotrichia, Listeria, Corynebacter, Satterella, Legionella, Treponema, Filifactor, Eubacterium, Streptococcus, Lactobacillus, Mycoplasma, Bacteroides, Flaviibora, Flavobacterium, Spherocheta , Azospirillum, Gluconacetobacter, Neisseria, Rosebria, Parvivacrum, Staphylococcus, Nitratifructor, Mycoplasma, and Campylobacter. Alternatively, said C2c2 effector protein is derived from Leptotrichia shaiii, L. selected from the group consisting of Weidii, Listeria ciligeri, Lachnospiraceae, Clostridium aminophyllum, Carnobacterium gallinarum, Pardibacter propionisigenes, Listeria weihenstephanensis, Listeriaceae, and Rhodobacter capsulata be done. In one particular embodiment, said C2c2 effector protein is L. Weedy F0279 or L.I. Weidi F0279 (Lw2) is a C2C2 effector protein.

In certain exemplary embodiments, said one or more guide RNAs are designed to bind to one or more target molecules used for diagnosis of disease states. In certain other exemplary embodiments, the disease state is infection, organ disease, blood disease, immune system disease, cancer, brain and nervous system disease, endocrine disease, pregnancy or childbirth related disease, genetic disease, or an environmental disease, cancer, fungal, bacterial, parasitic, or viral infection.

In certain exemplary embodiments, said RNA-based masking construct suppresses production of a detectable positive signal. Alternatively, the RNA-based masking construct suppresses production of a detectable positive signal by masking the detectable positive signal, or alternatively produces a detectable negative signal. Alternatively, said RNA-based masking construct comprises a silencing RNA that inhibits production of a gene product encoded by the reporting construct, producing a detectable positive signal upon expression of said gene product. Alternatively, said RNA-based masking construct is a ribozyme that produces said detectable negative signal, and said detectable positive signal is produced when said ribozyme is inactivated. In another exemplary embodiment, the ribozyme converts a substrate to a first state, and the substrate converts to a second state when the ribozyme is inactivated. Alternatively, said RNA-based masking factor is an aptamer, said aptamer sequestering an enzyme, said enzyme acting on a substrate to produce a detectable signal when released from said aptamer. Alternatively, the aptamer sequesters a pair of factors that bind to produce a detectable signal upon release from the aptamer. In a further embodiment, said RNA-based masking construct comprises an RNA oligonucleotide, a detectable ligand at a first end of said RNA oligonucleotide, and a masking moiety at a second end of said RNA oligonucleotide. Alternatively, said detectable ligand is a fluorophore and said masking moiety is a quenching molecule.

In certain exemplary embodiments, the methods, systems, and devices disclosed herein may be used to detect SNPs associated with fetal cerebellar myelosis. Exemplary fetal cerebellar myelosis mutations that may be detected using embodiments disclosed herein are disclosed in Yuan et al. Science 10.1126/science.aam7120 (2017).

These and other aspects, objects, features and advantages of the illustrative embodiments will be apparent to those of ordinary skill in the art after considering the detailed description of the illustrative illustrative embodiments that follows.

Schematic representation of an exemplary C2c2 system CRISPR effector system.

(A) Schematic representation of the CRISPR/C2c2 locus from Leptotorichia weedii. Representative crRNA structures from the LwC2c2 and LshC2c2 lines are shown (SEQ ID NOS: 142 and 143). (B) Schematic representation of an in vivo bacterial assay for C2c2 activity. Clone the protospacer upstream of the β-lactamase gene in an ampicillin resistant plasmid. This construct is transformed into E. coli expressing C2c2 with either the targeting spacer or the non-targeting spacer. The resulting transformants are counted to quantify the activity. (C) Quantitation of in vivo activity of LwC2c2 and LshC2c2 (n=2 biologically identical samples; bars represent mean±s.e.m.). (D) Final size exclusion gel filtration of LwC2c2. (E) Acrylamide gel stained with Coomassie blue of two-step purified LwC2c2. (F) Activity of LwC2c2 against different PFS targets. LwC2c2 was targeted to a fluorescent RNA with a variable 3' PFS flanked by spacers and reaction products were visualized on a denaturing gel. LwC2c2 showed a slight preference for the protospacer flanking site (PFS) G.

Detection of exemplary masking constructs at different dilutions (1:4, 1:16, 1:32, 1:64) using 1 μg, 100 ng, 10 ng, and 1 ng of target with four different amounts of protein/crRNA indicates Technically identical samples were prepared in duplicate using 2 sources of crRNA, no crRNA conditions and measured at 5 minute intervals over 3 hours in (96+48) x 2 = 288 reactions. Detection of exemplary masking constructs at different dilutions (1:4, 1:16, 1:32, 1:64) using 1 μg, 100 ng, 10 ng, and 1 ng of target with four different amounts of protein/crRNA indicates Technically identical samples were prepared in duplicate using 2 sources of crRNA, no crRNA conditions and measured at 5 minute intervals over 3 hours in (96+48) x 2 = 288 reactions. Detection of exemplary masking constructs at different dilutions (1:4, 1:16, 1:32, 1:64) using 1 μg, 100 ng, 10 ng, and 1 ng of target with four different amounts of protein/crRNA indicates Technically identical samples were prepared in duplicate using 2 sources of crRNA, no crRNA conditions and measured at 5 minute intervals over 3 hours in (96+48) x 2 = 288 reactions. Detection of exemplary masking constructs at different dilutions (1:4, 1:16, 1:32, 1:64) using 1 μg, 100 ng, 10 ng, and 1 ng of target with four different amounts of protein/crRNA indicates Technically identical samples were prepared in duplicate using 2 sources of crRNA, no crRNA conditions and measured at 5 minute intervals over 3 hours in (96+48) x 2 = 288 reactions.

FIG. 10 is a schematic of an exemplary detection scheme using masking constructs and CRISPR effector proteins according to certain exemplary embodiments;

1 is a set of graphs showing the time course of fluorescence during target detection with different sources of guide RNA.

FIG. 10 is a graph showing normalized fluorescence for different dilutions of target RNA with varying concentrations of CRISPR effector protein.

1 is a schematic diagram showing the general steps of a NASBA amplification reaction; FIG.

Graph showing detection of the nucleic acid target ssRNA1 amplified by NASBA with three different sets of primers and collateral detection of C2c2 with a quenching fluorescent probe (n=2 technically identical samples; bars indicate mean±s.e.m.).

FIG. 10 is a graph showing side effects that may be used to detect the presence of lentiviral target RNA. FIG.

Fig. 4 is a graph showing secondary effects and NASBA's ability to detect species at aM (= 10 ^-18 M) concentrations.

FIG. 10 is a graph showing rapid discrimination of low-concentration samples by side effects and NASBA. FIG.

FIG. 10 shows that the normalized fluorescence intensity at a particular time point is predictive of the input concentration of the sample. Fluorescence measurements from Casl3a detection performed without amplification correlate with input RNA concentration (n=2 biologically identical samples; bars indicate mean±s.e.m.).

Schematic of an RPA reaction, showing the components involved in the reaction.

Schematic representation of the SHERLOCK method (Specific High Sensitivity Enzymatic Reporter UnLOCKing) showing detection of both DNA or RNA targets by incorporation of RPA or RT-RPA steps. Upon recognizing the target RNA, a secondary effect causes C2c2 to cleave the cleavage reporter and produce fluorescence. A single molecule quantity of RNA or DNA can be amplified into DNA by recombinase polymerase amplification (RPA) and transcribed to produce RNA. This RNA is detected by C2c2.

Schematic representation of ssRNA targets (SEQ ID NOs: 144 and 145) detected by C2c2 secondary detection.

1 is a set of graphs showing single-molecule DNA detection (ie C2c2 addition within 15 minutes) using RPA.

1 is a set of graphs showing that adding T7 polymerase to RPA reactions adversely affects DNA detection.

1 is a set of graphs showing that adding polymerase to RPA reactions does not adversely affect DNA detection.

RPA, T7 transcription, and C2c2 detection reactions are compatible and achieve single-molecule detection when co-incubated (n=2 technically identical samples; bars are mean±s.e.m. ).

FIG. 10 is a set of graphs showing the effectiveness of short incubations of RPA-RNA.

1 is a set of graphs showing that increasing amounts of T7 polymerase increase sensitivity to RPA-RNA.

FIG. 10 is a set of graphs showing the results of an RPA-DNA detection assay using a one-pot reaction with 1.5x enzyme. Single molecule (2 aM) detection was achieved at a rate of 30 minutes.

A set of graphs showing that the RPA-DNA one-pot reaction has a quantitative decrease in fluorescence with input concentration. The fitted curve shows the relationship between the target input concentration and the output fluorescence intensity.

(A) C2c2 detection of RNA without amplification can detect ssRNA targets at concentrations up to 50 fM (n=2 technically identical samples; bars show mean±s.e.m.), (B) FIG. 2 is a set of graphs showing that the RPA-C2c2 reaction is capable of single-molecule DNA detection (n=4 technically identical samples; bars represent mean±s.e.m.).

4 is a set of graphs showing that the C2c2 signal generated by certain exemplary embodiments can detect 20 pM target on a paper substrate.

FIG. 10 is a graph showing that certain RNase inhibitors can eliminate paper background signal.

4 is a set of graphs showing detection on a glass fiber substrate using a system according to certain exemplary embodiments;

1 is a set of graphs showing the following. (A) Schematic of Zika RNA detection according to certain exemplary embodiments. Lentiviruses were packaged with Zika RNA or homologous dengue RNA fragments targeted by C2c2 secondary detection. Media was harvested after 48 hours for hot lysis, RT-RPA, and C2c2 detection. (B) RT-RAP-C2c2 detection is capable of very sensitive detection of dicarentiviral particles (n=4 technically identical samples, two-tailed Student's t-test; ****, p< 0.0001; bars indicate mean±s.e.m.). (C) Schematic of detection of Zika RNA on paper using freeze-dried C2c2, according to certain exemplary embodiments. (D) This paper-based assay can detect dicalentiviral particles with very high sensitivity (n=4 technically identical samples, two-tailed Student's t-test; ****, p< 0.0001; **, p<0.01, bars indicate mean±s.e.m.).

1 is a set of graphs showing the following. (A) Schematic for reverse transcription of Zika RNA isolated from human serum, degradation of RNA by RNase H, RPA of cDNA, and C2c2 detection. (B) C2c2 can detect human deer serum samples very sensitively. Concentrations of Zika RNA indicated were confirmed by quantitative PCR (n=4 technically identical samples, two-tailed Student's t-test; ****, p<0.0001; bars represent mean ± s.e.m. show).

1 is a set of graphs showing the following. (A) Freeze-dried C2c2 can detect ssRNA1 with high sensitivity at concentrations as low as femtomoles. C2c2 can rapidly detect ssRNA1 target in liquid form (B) or freeze-dried (C) at 200 pM on paper. This reaction is capable of sensitive detection of synthetic Zika RNA fragments in solution (D) (n=3) and freeze-dried form (E) (n=3). (F) Quantitation curve of deer cDNA detection showing significant correlation between input concentration and detected fluorescence. (G) C2c2 detection of ssRNA1 in the presence of varying amounts of human serum (n=2 technically identical samples unless otherwise stated; bars represent mean±s.e.m.).

(A) Outlines C2c2 detection of 16S rRNA genes from bacterial genomes using a set of universal V3 RPA primers. (B) E. coli or Pseudomonas aeruginosa gDNA can be detected with high sensitivity and specificity using assays performed according to certain exemplary embodiments (n=4 technically identical samples, two-sided Student's t- Test; ***, p<0.0001; bars show mean±s.e.m.). Ec, Escherichia coli; Kp, Klebsiella pneumoniae; Pa, Pseudomonas aeruginosa; Mt, Mycobacterium tuberculosis; Sa, Staphylococcus yellow

1 is a set of graphs showing the following. (A) Detect two different carbapenem resistance genes (KPC and NDM-1) from four different clinical isolates of Klebsiella pneumoniae. (B) Detection of the carbapenem resistance gene (part A) is normalized as signal ratio with KPC and NDM-1 crRNA assays (n=2 technically identical samples, two-tailed Student's t-test; ** **, p<0.0001; bars indicate mean±s.e.m.).

1 is a set of graphs showing the following. (A) C2c2 is not sensitive to a single mismatch, but can discriminate a single base difference in the target when loaded with crRNAs with additional mismatches. ssRNA targets 1-3 were detected using 11 crRNAs with 10 spacers containing synthetic mismatches at various positions in the crRNA. Mismatched spacers did not reduce cleavage of target 1 but inhibited cleavage of mismatched targets 2 and 3 (SEQ ID NOS: 146-159). (B) Schematic showing the rational design process for single-base-specific spacers with synthetic mismatches. Synthetic discrepancies are located near the SNP or base of interest (SEQ ID NOS: 160-164). (C) Highly specific detection of SNP strains using C2c2 detection with truncated (23-nucleotide) crRNA to detect single-nucleotide differences between Zika African and Zika America RNA targets. distinguishable (n=2 technically identical samples, one-tailed Student's t-test; *, p<0.05; ****, p<0.0001; bars indicate mean±s.e.m.) .

1 is a set of graphs showing the following. (A) Schematic showing the Zika strain target regions and crRNA sequences (SEQ ID NOs: 165-170) used for detection. Target SNPs are highlighted in red or blue, and mismatches due to guide sequence synthesis are shown in red. (B) Highly specific detection of strain SNPs allows SHERLOCK to be used to distinguish between African deer strain RNA targets and American deer strain RNA targets (n=2 technically identical samples, Two-tailed Student's t-test; ****, p<0.0001; bars indicate mean±s.e.m.) (SEQ ID NOS: 171-176). (C) Schematic diagram showing target regions and crRNA sequences of dengue strains used for detection. Target SNPs are highlighted in red or blue, and mismatches due to guide sequence synthesis are shown in red. (D) Highly specific detection of strain SNPs allows SHERLOCK to distinguish between dengue strain 1 and dengue strain 3 RNA targets (n=2 technically identical samples, Two-tailed Student's t-test; ***, p<0.0001; bars indicate mean±s.e.m.). (Fig. 37)

1 is a set of graphs showing the following. (A) Circos diagram showing the positions of human SNPs detected in C2c2. (B) Assays performed according to certain exemplary embodiments can distinguish between human SNPs. SHERLOCK can accurately identify the genotypes of 4 different individuals at 4 different SNP sites in the human genome. The genotype of each person and the identity of the crRNA sensing allele are annotated below each figure (n=4 technically identical samples; two-tailed Student's t-test; *, p<0. **, p<0.01; ***, p<0.001; ***, p<0.0001; bars indicate mean±s.e.m.). (C) Schematic representation of a cfDNA detection process, such as circulating cell-free DNA detection of cancer mutations, according to certain exemplary embodiments. (D) Exemplary crRNA sequences for detecting EGFR L858R and BRAF V600E (SEQ ID NOS:177-182). Sequences of two genomic loci assayed for cancer mutations in circulating cell-free DNA. In these target genomic sequences, SNPs are highlighted in blue and mutant/wild-type sensing crRNA sequences with synthetic mismatches are shown in red.

A set of graphs showing that C2c2 can detect mutant low frequency alleles in pseudocirculating cell-free DNA samples derived from EGFR L858R (C) or BRAF V600E (B) low frequency alleles (n= Four technically identical samples, two-tailed Student's t-test; *, p<0.05; **, p<0.01, ****, P<0.0001; bars indicate ± standard error) .

1 is a set of graphs showing the following. (A) The assay can distinguish genotypes at rs5082 (n=4 technically identical samples; *, p<0.05; **, p<0.01; ***, p<0 ***, p<0.0001; bars indicate mean±s.e.m.). (B) This assay can distinguish gDNA genotypes at rs601338 directly from centrifuged, denatured, and boiled saliva (n=3 technically identical samples; *, p<0 .05; bars indicate mean±s.e.m.).

(A) Schematic of an exemplary embodiment performed on ssDNA1 in a different target background than ssDNA1 with only one mismatch. (B) The assay detects ssDNA1 in a single base-specific manner in the presence of a mismatched background (a target that differs from ssDNA by only one mismatch). Various concentrations of target DNA were mixed with excess background DNA with one mismatch and detected by the assay.

FIG. 10 is a graph showing that effective detection can be achieved with masking constructs with different dyes Cy5.

Schematic representation of a gold nanoparticle colorimetric assay. Gold nanoparticles are aggregated using a combination of DNA linkers and RNA bridges. Upon addition of RNase activity, the ssRNA bridges are cleaved, releasing the gold nanoparticles and producing a characteristic color change to red.

Fig. 10 is a graph showing the ability to detect color change of dispersed nanoparticles at 520nm. The nanoparticles were dispersed with RNase A added at various concentrations according to the exemplary embodiment shown in FIG.

FIG. 10 is a graph showing that the RNase colorimetric test is quantitative.

Figure 3 is an image of a microwell plate showing that the color change of dispersed nanoparticles is visually detectable.

1 is an image showing that colorimetric changes can be seen on a paper substrate. The test was performed at 37° C. for 10 minutes on a glass fiber 934-AH surface.

1 is a schematic diagram of a conformation switching aptamer for detecting proteins or small molecules according to certain exemplary embodiments; FIG. The ligated product (B) is used as the perfect target for the RNA target effector. RNA target effectors are unable to detect unligated input (SEQ ID NOs:202 and 424).

Gel images showing that aptamer-based ligation can create RPA-detectable substrates. Aptamers were incubated with various concentrations of thrombin and ligated to the probe. The ligated construct was used as template for a 3 minute RPA reaction. 500 nM thrombin contained a much higher concentration of amplified target than background.

The amino acid sequences of the HEPN domains of selected C2c2 orthologues are shown (SEQ ID NOs:204-233).

Detection of RNA by Cas13a using RPA amplification (SHERLOCK) can detect ssRNA targets at concentrations up to about 2 aM compared to Cas13a alone (n = 4 technically identical samples; bars mean ± s.e.m. shown).

Detection by Casl3a can be used to sense viral and bacterial pathogens. (A) Schematic of SHERLOCK detection of ZIKV RNA isolated from human clinical samples. (B) SHERLOCK can detect human ZIKV-positive serum (S) or urine (U) samples with very high sensitivity. Approximate concentrations of ZIKV RNA shown were determined by quantitative PCR (n=4 technically identical samples, two-tailed Student's t-test; ***, p<0.0001; bars are mean±s.e.m. nd indicates "not detected").

Comparison of detection of ssRNA1 by NASBA and SHERLOCK using primer set 2 (Fig. 11) (n = 2 technically identical samples; bars show mean ± standard error).

Nucleic acid amplification by RPA and one reaction SHERLOCK. (A) Digital droplet PCR quantification of ssRNA1 performed on the dilutions used in Figure 1C. Adjusted concentrations of diluents based on ddPCR results are shown in the top bar graph. (B) Digital droplet PCR quantification of ssDNA1 performed on the dilutions used in FIG. 1D. Adjusted concentrations of diluents based on ddPCR results are shown in the top bar graph. (C) RPA, T7-mediated transcription, and Casl3a-mediated detection reactions are compatible and achieve single-molecule detection of DNA2 when co-incubated (n=3 technically identical samples, two-tailed Student's t-test; ns indicate "not significant"; **, p<0.01; ****, p<0.0001; bars indicate mean±s.e.m.). Nucleic acid amplification by RPA and one reaction SHERLOCK. (A) Digital droplet PCR quantification of ssRNA1 performed on the dilutions used in Figure 1C. Adjusted concentrations of diluents based on ddPCR results are shown in the top bar graph. (B) Digital droplet PCR quantification of ssDNA1 performed on the dilutions used in FIG. 1D. Adjusted concentrations of diluents based on ddPCR results are shown in the top bar graph. (C) RPA, T7-mediated transcription, and Casl3a-mediated detection reactions are compatible and achieve single-molecule detection of DNA2 when co-incubated (n=3 technically identical samples, two-tailed Student's t-test; ns indicate "not significant"; **, p<0.01; ****, p<0.0001; bars indicate mean±s.e.m.).

Comparison of SHERLOCK with other highly sensitive nucleic acid detection tools. (A) Detection analysis of serial ssDNA1 dilutions by digital droplet PCR (n=4 technically identical samples, two-tailed Student's t-test; n.s. indicates "not significant"; *, p **, p<0.01;****, p<0.0001;red line indicates mean, bars indicate mean ± s.e.m.Samples less than 10 ⁻¹ measured copies number/μL of sample not shown). (B) Detection analysis of serial ssDNA1 dilutions by quantitative PCR (n=16 technically identical samples, two-tailed Student's t-test; n.s. indicates "not significant"; **, p< ***, p<0.0001; red line indicates mean, bars indicate mean ± standard error, samples with relative signal less than ^{10 −10} not shown). (C) Detection analysis of serial ssDNA1 dilutions by RPA using SYBR Green II (n=4 technically identical samples, two-tailed Student's t-test; *, p<0.05; **, p<0.01; red line indicates mean, bars indicate mean ± standard error, samples with relative signal less than ¹⁰⁰ not shown). (D) Detection analysis of serial ssDNA1 dilutions by SHERLOCK (n=4 technically identical samples, two-tailed Student's t-test; **, p<0.01; ****, p<0.0001 red line indicates mean, bars indicate mean ± standard error, samples with relative signal less than ¹⁰⁰ not shown). (E) Percentage coefficient of variation of serial ssDNA1 dilutions for the four detection methods. (F) Mean percent coefficient of variation of ssDNA1 dilutions of 6e2, 6e1, 6e0, and 6e-1 for the four detection methods (bars show mean±s.e.m.). Comparison of SHERLOCK with other highly sensitive nucleic acid detection tools. (A) Detection analysis of serial ssDNA1 dilutions by digital droplet PCR (n=4 technically identical samples, two-tailed Student's t-test; n.s. indicates "not significant"; *, p **, p<0.01;****, p<0.0001;red line indicates mean, bars indicate mean ± s.e.m.Samples less than 10 ⁻¹ measured copies number/μL of sample not shown). (B) Detection analysis of serial ssDNA1 dilutions by quantitative PCR (n=16 technically identical samples, two-tailed Student's t-test; n.s. indicates "not significant"; **, p< ***, p<0.0001; red line indicates mean, bars indicate mean ± standard error, samples with relative signal less than ^{10 −10} not shown). (C) Detection analysis of serial ssDNA1 dilutions by RPA using SYBR Green II (n=4 technically identical samples, two-tailed Student's t-test; *, p<0.05; **, p<0.01; red line indicates mean, bars indicate mean ± standard error, samples with relative signal less than ¹⁰⁰ not shown). (D) Detection analysis of serial ssDNA1 dilutions by SHERLOCK (n=4 technically identical samples, two-tailed Student's t-test; **, p<0.01; ****, p<0.0001 red line indicates mean, bars indicate mean ± standard error, samples with relative signal less than ¹⁰⁰ not shown). (E) Percentage coefficient of variation of serial ssDNA1 dilutions for the four detection methods. (F) Mean percent coefficient of variation of ssDNA1 dilutions of 6e2, 6e1, 6e0, and 6e-1 for the four detection methods (bars show mean±s.e.m.). Comparison of SHERLOCK with other highly sensitive nucleic acid detection tools. (A) Detection analysis of serial ssDNA1 dilutions by digital droplet PCR (n=4 technically identical samples, two-tailed Student's t-test; n.s. indicates "not significant"; *, p **, p<0.01;****, p<0.0001;red line indicates mean, bars indicate mean ± s.e.m.Samples less than 10 ⁻¹ measured copies number/μL of sample not shown). (B) Detection analysis of serial ssDNA1 dilutions by quantitative PCR (n=16 technically identical samples, two-tailed Student's t-test; n.s. indicates "not significant"; **, p< ***, p<0.0001; red line indicates mean, bars indicate mean ± standard error, samples with relative signal less than ^{10 −10} not shown). (C) Detection analysis of serial ssDNA1 dilutions by RPA using SYBR Green II (n=4 technically identical samples, two-tailed Student's t-test; *, p<0.05; **, p<0.01; red line indicates mean, bars indicate mean ± standard error, samples with relative signal less than ¹⁰⁰ not shown). (D) Detection analysis of serial ssDNA1 dilutions by SHERLOCK (n=4 technically identical samples, two-tailed Student's t-test; **, p<0.01; ****, p<0.0001 red line indicates mean, bars indicate mean ± standard error, samples with relative signal less than ¹⁰⁰ not shown). (E) Percentage coefficient of variation of serial ssDNA1 dilutions for the four detection methods. (F) Mean percent coefficient of variation of ssDNA1 dilutions of 6e2, 6e1, 6e0, and 6e-1 for the four detection methods (bars show mean±s.e.m.). Detection of carbapenem resistance in clinical bacterial isolates. Detection of two different carbapenem resistance genes (KPC and NDM-1) from five clinical isolates of Klebsiella pneumoniae and an E. coli control (n=4 technically identical samples, two-tailed Student's t-test; *** *, p<0.0001; bars indicate mean±s.e.m.; n.d. indicates "not detected").

Analysis of the sensitivity of LwCasl3a to cleaved spacers and single mismatches in target sequences. (A) are the truncated spacer crRNA sequences (SEQ ID NOs:425-436) used in (B)-(G). Also shown are the sequences of ssRNA1 and ssRNA2 with a single base pair difference shown in red. crRNAs containing synthetic mismatches are shown with mismatched positions in red. (B) Secondary cleavage activity of 28 nucleotide (nt) spacer crRNAs with synthetic mismatches at positions 1-7 against ssRNAs 1 and 2 (n=4 technically identical samples; bars show mean±s.e.m.). . (C) Specificity ratios of crRNAs tested in (B). Specificity ratios are calculated as the ratio of target RNA (ssRNA1) secondary cleavage to non-target RNA (ssRNA2) secondary cleavage (n=4 technically identical samples; bars represent mean±SEM). (D) Secondary cleavage activity of 23-nt spacer crRNAs with synthetic mismatches at positions 1-7 against ssRNAs 1 and 2 (n=4 technically identical samples; bars show mean±s.e.m.). (E) Specificity ratios of crRNAs tested in (D). Specificity ratios are calculated as the ratio of secondary cleavage of target RNA (ssRNA1) to secondary cleavage of non-target RNA (ssRNA2) (n=4 technically identical samples; bars show mean±SEM). (F) Secondary cleavage activity against ssRNA1 and ssRNA2 of 20-nt spacer crRNAs with synthetic mismatches at positions 1-7 (n=4 technically identical samples; bars show mean±s.e.m.). (G) Specificity ratios of crRNAs tested in (F). Specificity ratios are calculated as the ratio of secondary cleavage of target RNA (ssRNA1) to secondary cleavage of non-target RNA (ssRNA2) (n=4 technically identical samples; bars show mean±SEM). Analysis of the sensitivity of LwCasl3a to cleaved spacers and single mismatches in target sequences. (A) are the truncated spacer crRNA sequences (SEQ ID NOs:425-436) used in (B)-(G). Also shown are the sequences of ssRNA1 and ssRNA2 with a single base pair difference shown in red. crRNAs containing synthetic mismatches are shown with mismatched positions in red. (B) Secondary cleavage activity of 28 nucleotide (nt) spacer crRNAs with synthetic mismatches at positions 1-7 against ssRNAs 1 and 2 (n=4 technically identical samples; bars show mean±s.e.m.). . (C) Specificity ratios of crRNAs tested in (B). Specificity ratios are calculated as the ratio of target RNA (ssRNA1) secondary cleavage to non-target RNA (ssRNA2) secondary cleavage (n=4 technically identical samples; bars represent mean±SEM). (D) Secondary cleavage activity of 23-nt spacer crRNAs with synthetic mismatches at positions 1-7 against ssRNAs 1 and 2 (n=4 technically identical samples; bars show mean±s.e.m.). (E) Specificity ratios of crRNAs tested in (D). Specificity ratios are calculated as the ratio of secondary cleavage of target RNA (ssRNA1) to secondary cleavage of non-target RNA (ssRNA2) (n=4 technically identical samples; bars show mean±SEM). (F) Secondary cleavage activity against ssRNA1 and ssRNA2 of 20-nt spacer crRNAs with synthetic mismatches at positions 1-7 (n=4 technically identical samples; bars show mean±s.e.m.). (G) Specificity ratios of crRNAs tested in (F). Specificity ratios are calculated as the ratio of secondary cleavage of target RNA (ssRNA1) to secondary cleavage of non-target RNA (ssRNA2) (n=4 technically identical samples; bars show mean±SEM). Analysis of the sensitivity of LwCasl3a to cleaved spacers and single mismatches in target sequences. (A) are the truncated spacer crRNA sequences (SEQ ID NOs:425-436) used in (B)-(G). Also shown are the sequences of ssRNA1 and ssRNA2 with a single base pair difference shown in red. crRNAs containing synthetic mismatches are shown with mismatched positions in red. (B) Secondary cleavage activity of 28 nucleotide (nt) spacer crRNAs with synthetic mismatches at positions 1-7 against ssRNAs 1 and 2 (n=4 technically identical samples; bars show mean±s.e.m.). . (C) Specificity ratios of crRNAs tested in (B). Specificity ratios are calculated as the ratio of target RNA (ssRNA1) secondary cleavage to non-target RNA (ssRNA2) secondary cleavage (n=4 technically identical samples; bars represent mean±SEM). (D) Secondary cleavage activity of 23-nt spacer crRNAs with synthetic mismatches at positions 1-7 against ssRNAs 1 and 2 (n=4 technically identical samples; bars show mean±s.e.m.). (E) Specificity ratios of crRNAs tested in (D). Specificity ratios are calculated as the ratio of secondary cleavage of target RNA (ssRNA1) to secondary cleavage of non-target RNA (ssRNA2) (n=4 technically identical samples; bars represent mean±SEM). (F) Secondary cleavage activity against ssRNA1 and ssRNA2 of 20-nt spacer crRNAs with synthetic mismatches at positions 1-7 (n=4 technically identical samples; bars show mean±s.e.m.). (G) Specificity ratios of crRNAs tested in (F). Specificity ratios are calculated as the ratio of secondary cleavage of target RNA (ssRNA1) to secondary cleavage of non-target RNA (ssRNA2) (n=4 technically identical samples; bars represent mean±SEM). Analysis of the sensitivity of LwCasl3a to cleaved spacers and single mismatches in target sequences. (A) are the truncated spacer crRNA sequences (SEQ ID NOs:425-436) used in (B)-(G). Also shown are the sequences of ssRNA1 and ssRNA2 with a single base pair difference shown in red. crRNAs containing synthetic mismatches are shown with mismatched positions in red. (B) Secondary cleavage activity of 28 nucleotide (nt) spacer crRNAs with synthetic mismatches at positions 1-7 against ssRNAs 1 and 2 (n=4 technically identical samples; bars show mean±s.e.m.). . (C) Specificity ratios of crRNAs tested in (B). Specificity ratios are calculated as the ratio of target RNA (ssRNA1) secondary cleavage to non-target RNA (ssRNA2) secondary cleavage (n=4 technically identical samples; bars represent mean±SEM). (D) Secondary cleavage activity of 23-nt spacer crRNAs with synthetic mismatches at positions 1-7 against ssRNAs 1 and 2 (n=4 technically identical samples; bars show mean±s.e.m.). (E) Specificity ratios of crRNAs tested in (D). Specificity ratios are calculated as the ratio of secondary cleavage of target RNA (ssRNA1) to secondary cleavage of non-target RNA (ssRNA2) (n=4 technically identical samples; bars show mean±SEM). (F) Secondary cleavage activity against ssRNA1 and ssRNA2 of 20-nt spacer crRNAs with synthetic mismatches at positions 1-7 (n=4 technically identical samples; bars show mean±s.e.m.). (G) Specificity ratios of crRNAs tested in (F). Specificity ratios are calculated as the ratio of secondary cleavage of target RNA (ssRNA1) to secondary cleavage of non-target RNA (ssRNA2) (n=4 technically identical samples; bars show mean±SEM).

Identification of ideal synthetic mismatch positions for mutations in the target sequence. (A) Sequences (SEQ ID NOS: 437-462) for evaluating ideal synthetic mismatch positions to detect mutations between ssRNA1 and ssRNA2. In each of these targets, crRNAs with synthetic mismatches at red positions were tested. Each pair of synthetic mismatched crRNAs is designed so that the mutation position is offset relative to the sequence of the spacer. The spacer is designed to assess mutations at positions 3, 4, 5, and 6 within the spacer. (B) Secondary cleavage activity against ssRNAs 1 and 2 of crRNAs with synthetic mismatches at various positions. Spacer: There are 4 sets of crRNAs with mutations at positions 3, 4, 5, or 6 within the target double-stranded region (n=4 technically identical samples; bars show mean±s.e.m.). (C) Specificity ratios of crRNAs tested in (B). Specificity ratios are calculated as the ratio of secondary cleavage of target RNA (ssRNA1) to secondary cleavage of non-target RNA (ssRNA2) (n=4 technically identical samples; bars show mean±SEM). Identification of ideal synthetic mismatch positions for mutations in the target sequence. (A) Sequences (SEQ ID NOS: 437-462) for evaluating ideal synthetic mismatch positions to detect mutations between ssRNA1 and ssRNA2. In each of these targets, crRNAs with synthetic mismatches at red positions were tested. Each pair of synthetic mismatched crRNAs is designed so that the mutation position is offset relative to the sequence of the spacer. The spacer is designed to assess mutations at positions 3, 4, 5, and 6 within the spacer. (B) Secondary cleavage activity against ssRNAs 1 and 2 of crRNAs with synthetic mismatches at various positions. Spacer: There are 4 sets of crRNAs with mutations at positions 3, 4, 5, or 6 within the target double-stranded region (n=4 technically identical samples; bars show mean±s.e.m.). (C) Specificity ratios of crRNAs tested in (B). Specificity ratios are calculated as the ratio of secondary cleavage of target RNA (ssRNA1) to secondary cleavage of non-target RNA (ssRNA2) (n=4 technically identical samples; bars show mean±SEM).

Genotyping by SHERLOCK at additional loci and direct genotyping from boiled saliva. SHERLOCK can discriminate genotypes at the rs601338 SNP site in genomic DNA directly from centrifuged, denatured, and boiled saliva (n=4 technically identical samples, two-tailed Student's t-test; **, p<0.01; ****, p<0.001; bars indicate mean±s.e.m.).

Development of synthetic genotyping standards to accurately genotype human SNPs. (A) Genotyped by SHERLOCK at the rs601338 SNP site and compared to PCR-amplified genotype references for each of the 4 individuals (n=4 technically identical samples; bars represent mean±s.e.m. ). (B) Genotyped by SHERLOCK at the rs4363657 SNP site and compared to PCR-amplified genotype references for each of the four individuals (n=4 technically identical samples; bars represent mean±s.e.m. ). (C) Heat map of p-values calculated for individual SHERLOCK results at the rs601338 SNP site and synthetic criteria. A heat map is shown for each of the crRNA sensing alleles. Color heatmaps are scaled so that insignificant (p>0.05) are in red and significant (p<0.05) are in blue (n=4 technical Same samples, one-way ANOVA). (D) Heatmap of p-values calculated for individual SHERLOCK results at the rs4363657 SNP site and synthetic criteria. A heat map is shown for each of the crRNA sensing alleles. Color heatmaps are scaled so that insignificant (p>0.05) are in red and significant (p<0.05) are in blue (n=4 technical Same samples, one-way ANOVA). (E) Guide to understanding the heat map of p-values for SHERLOCK genotyping. Selecting alleles corresponding to p-values greater than 0.05 between individuals and allele synthesis standards can be readily genotyped. Red blocks correspond to non-significant differences between the synthetic reference and individual SHERLOCK results, and thus correspond to positive genotype results. Blue blocks correspond to significant differences between the synthetic standard and solid SHERLOCK results, and thus genotype-negative results. Development of synthetic genotyping standards to accurately genotype human SNPs. (A) Genotyped by SHERLOCK at the rs601338 SNP site and compared to PCR-amplified genotype references for each of the 4 individuals (n=4 technically identical samples; bars represent mean±s.e.m. ). (B) Genotyped by SHERLOCK at the rs4363657 SNP site and compared to PCR-amplified genotype references for each of the four individuals (n=4 technically identical samples; bars represent mean±s.e.m. ). (C) Heat map of p-values calculated for individual SHERLOCK results at the rs601338 SNP site and synthetic criteria. A heat map is shown for each of the crRNA sensing alleles. Color heatmaps are scaled so that insignificant (p>0.05) are in red and significant (p<0.05) are in blue (n=4 technical Same samples, one-way ANOVA). (D) Heatmap of p-values calculated for individual SHERLOCK results at the rs4363657 SNP site and synthetic criteria. A heat map is shown for each of the crRNA sensing alleles. Color heatmaps are scaled so that insignificant (p>0.05) are in red and significant (p<0.05) are in blue (n=4 technical Same samples, one-way ANOVA). (E) Guide to understanding the heat map of p-values for SHERLOCK genotyping. Selecting alleles corresponding to p-values greater than 0.05 between individuals and allele synthesis standards can be readily genotyped. Red blocks correspond to non-significant differences between the synthetic reference and individual SHERLOCK results, and thus correspond to positive genotype results. Blue blocks correspond to significant differences between the synthetic standard and solid SHERLOCK results, and thus genotype-negative results.

Detection of ssDNA1 as a background target with a small fraction of mismatches. Serial dilutions of ssDNA1 were detected with SHERLOCK in the background of human genomic DNA. Note that there was no sequence similarity between the detected ssDNA1 target and background genomic DNA (n=2 technically identical samples; bars show mean±s.e.m.).

Urine (A) or serum (B) samples from Zika virus patients were heat inactivated at 95° C. (urine) or 65° C. (serum) for 5 minutes. According to one exemplary embodiment, 1 microliter of inert urine or serum was used as input for a 2 hour RPA reaction followed by a 3 hour C2c2/Casl3a detection reaction. Error bars indicate 1 standard deviation (SD) based on n=4 technically identical samples of the detection reaction.

Urine samples from Zika virus patients were heat inactivated at 95° C. for 5 minutes. According to an exemplary embodiment, 1 microliter of inactivated urine was used as input for a 30 minute RPA reaction followed by (A) 3 hours or (B) 1 hour later C2c2/Casl3 detection reactions. Error bars indicate 1 SD based on n=4 technically identical samples of detection reactions.

Urine samples from Zika virus patients were heat inactivated at 95° C. for 5 minutes. One microliter of inactivated urine was used as input for a 20 minute RPA reaction followed by a 1 hour C2c2/Casl3a detection reaction. Healthy human urine was used as a negative control. Error bars indicate 1 SD based on n=4 technically identical samples of detection reactions.

Urine samples from Zika virus patients were heat inactivated at 95° C. for 5 minutes. One microliter of inactivated urine was used as input for a 20 minute RPA reaction followed by a 1 hour C2c2/Casl3a detection reaction in the presence or absence of guide RNA. Data are normalized by removing the mean fluorescence value of the unguided detection reaction from the detection reaction containing the guide. Healthy human urine was used as a negative control. Error bars indicate 1 SD based on n=4 technically identical samples of detection reactions.

Detection of two malaria-specific targets with four different guide RNA designs according to exemplary embodiments (SEQ ID NOs:463-474).

Locations of design guide RNAs along the segmented LCMV genome are shown. Guide RNAs S1-S6 are complementary to MCMV S RNA (of which S1 and S6 bind to the 5' untranslated region (UTR) and 3' untranslated region, respectively). Guide RNAs L1-L6 are complementary to MCMV L RNA (of which L1 and L6 bind to the 5' and 3' untranslated regions, respectively). All guide RNAs bind to the coding strand.

Expression of Casl3a and LCMV-specific guide RNA increases LCMV replication in cell culture. A) HEK293FT cells were transfected with a plasmid expressing Casl3a and single-stranded guide RNA targeting LCMV or a non-targeting control. Twenty-four hours after transfection, cells were infected at a multiplicity of 5 with LCMV. Viral RNA in culture supernatants was subjected to RT-quantitative PCR 48 hours post-infection to determine virus titers. B) Inhibition of viral replication. Empty vector, non-target #1 and non-target #2 are considered negative controls. S1-S5 and L1-L6 target different regions of the LCMV genome. Error bars indicate 1 standard deviation based on n=3-6 biologically identical samples.

Inhibition of viral replication. LCMV-infected mammalian 293FT cells were transfected with the indicated C2c2 and guide plasmids. The table presents RT-quantitative PCR values as genomic equivalents per microliter, with bars representing each guide plasmid transfected. Empty vector, non-target #1 and non-target #2 are considered negative controls. S1-S5 and L1-L6 target different regions of the LCMV genome. Error bars indicate 1 standard deviation based on n=6 biologically identical samples.

Combining multiple guides increases Casl3a-mediated inhibition of LCMV replication. HEK293FT cells are transfected with a plasmid expressing Casl3a and one or more guide RNAs targeting LCMV or a non-targeting control. Twenty-four hours after transfection, LCMV infection was performed at a multiplicity of infection of 5, and virus titers were determined by RT-qPCR of viral RNA in culture supernatants 48 hours after infection. Empty vector, non-target #1 and non-target #2 are considered negative controls. Error bars indicate 1 standard deviation based on n=6 biologically identical samples. [00100] A guide fraction that reduces viral replication. For all guides, mean green fluorescent protein (GFP) fluorescence intensity 48 hours after LCMV infection was calculated from the same three samples. The fold change for each LCMV target guide was calculated as the ratio of the mean fluorescence comparing the control and LCMV target guides. P-values were calculated using a two-tailed unpaired test. A target guide is considered any guide with a p-value of 0.05 or less and a fold change (FC) of 2 or greater. The pie chart plots the tabulated data with wedges corresponding to the non-coding and coding regions of the four proteins of LCMV. The remaining guides are LCMV target guides that do not meet the p-value and FC thresholds.

Target efficiency distribution of the target guide. The distribution of fold change in GFP fluorescence (comparing control and LCMV target guides) is shown for guides meeting a p-value threshold of 0.05. Although not shown in this graph, 8 guides showed >50-fold reduction in GFP fluorescence (*8 guides showed >50-fold reduction).

Representative images (3 identical samples for each guide) of guides (#104) targeting the L coding region showing reduced GFP (ie LCMV replication) compared to controls (empty guide vector) are shown. Images were taken at 4x magnification 48 hours after LCMV infection. The fold change was 2.72 with a p-value of 0.047.

Shown is the fold change in GFP fluorescence compared to control and LCMV-targeted guides 48 hours post infection for all guides meeting a p-value threshold of 0.05 and a fold-change threshold of 2. Each position on the x-axis is a guide tested in the LCMV full genome screen. Guides that did not meet this threshold were plotted as 1's. The fold change of any guide with fluorescence below background noise is set as the maximum fold change observed.

The Casl3a diagnostic method can detect Zika virus nucleic acid with high sensitivity. Zika virus cDNA was serially diluted in healthy human urine and water to inactivate endogenous human RNAse and viral cDNA was quantified using the SHERLOCK test protocol (a). We also tested several cDNA samples from patient urine or serum (b). Combinations of guide RNA were used to differentiate patient samples from different countries during the Zika virus outbreak (c). Error bars indicate 1 standard deviation. Abbreviations: DOM = Dominican Republic, DOMUSA = Dominican Republic/United States, HND = Honduras, USA = United States.

FIG. 10 is a graph showing single copy detection of Zika according to certain exemplary embodiments; FIG.

Detection limits for Zika cDNA (a), RNA (b), and viral particles (c) by the SHERLOCK method using Zika virus-specific RPA primers and Zika virus-specific crRNA are shown. Error bars indicate 1 standard deviation of 3 technically identical samples. None of the inputs were water or urine plus nuclease-free water. Detection limits for Zika cDNA (a), RNA (b), and viral particles (c) by the SHERLOCK method using Zika virus-specific RPA primers and Zika virus-specific crRNA are shown. Error bars indicate 1 standard deviation of 3 technically identical samples. None of the inputs were water or urine plus nuclease-free water. Detection limits for Zika cDNA (a), RNA (b), and viral particles (c) by the SHERLOCK method using Zika virus-specific RPA primers and Zika virus-specific crRNA are shown. Error bars indicate 1 standard deviation of 3 technically identical samples. None of the inputs were water or urine plus nuclease-free water.

Panel A is a schematic of detecting single nucleotide mutations in virus samples. Panel B is a schematic showing the genomic locations of the three SNPs tested with the SHERLOCK method. Panel C shows a graph depicting the SNPs that occurred during the 2015 Zika virus outbreak along with the regions where the SNPs occurred. Panel D shows the fluorescence intensity ratio of mutant cRNA to wild-type cRNA at 1 hour. Panel E is a heatmap showing the log ₂ transformed ratio of the fluorescence intensity shown in Figure 78D for each sample against each of the crRNAs. Values greater than 0 indicate the presence of mutant variants. Panel F is a graph showing data with the S139N manifold. Dark-shaded bars indicate fluorescence measured when S139N-targeted crRNA is used in the detection reaction, and light-shaded bars indicate fluorescence measured when N139S-targeted crRNA is used. Error bars indicate 1 SD for three technically identical samples. Panel A is a schematic of detecting single nucleotide mutations in virus samples. Panel B is a schematic showing the genomic locations of the three SNPs tested with the SHERLOCK method. Panel C shows a graph depicting the SNPs that occurred during the 2015 Zika virus outbreak along with the regions where the SNPs occurred. Panel D shows the fluorescence intensity ratio of mutant cRNA to wild-type cRNA at 1 hour. Panel E is a heatmap showing the log ₂ transformed ratio of the fluorescence intensity shown in Figure 78D for each sample against each of the crRNAs. Values greater than 0 indicate the presence of mutant variants. Panel F is a graph showing data with the S139N manifold. Dark-shaded bars indicate fluorescence measured when S139N-targeted crRNA is used in the detection reaction, and light-shaded bars indicate fluorescence measured when N139S-targeted crRNA is used. Error bars indicate 1 SD for three technically identical samples. Panel A is a schematic of detecting single nucleotide mutations in virus samples. Panel B is a schematic showing the genomic locations of the three SNPs tested with the SHERLOCK method. Panel C shows a graph depicting the SNPs that occurred during the 2015 Zika virus outbreak along with the regions where the SNPs occurred. Panel D shows the fluorescence intensity ratio of mutant cRNA to wild-type cRNA at 1 hour. Panel E is a heatmap showing the log ₂ transformed ratio of the fluorescence intensity shown in Figure 78D for each sample against each of the crRNAs. Values greater than 0 indicate the presence of mutant variants. Panel F is a graph showing data with the S139N manifold. Dark-shaded bars indicate fluorescence measured when S139N-targeted crRNA is used in the detection reaction, and light-shaded bars indicate fluorescence measured when N139S-targeted crRNA is used. Error bars indicate 1 SD for three technically identical samples. Panel A is a schematic of detecting single nucleotide mutations in virus samples. Panel B is a schematic showing the genomic locations of the three SNPs tested with the SHERLOCK method. Panel C shows a graph depicting the SNPs that occurred during the 2015 Zika virus outbreak along with the regions where the SNPs occurred. Panel D shows the fluorescence intensity ratio of mutant to wild-type cRNA at 1 hour. Panel E is a heatmap showing the log ₂ transformed ratio of the fluorescence intensity shown in Figure 78D for each sample against each of the crRNAs. Values greater than 0 indicate the presence of mutant variants. Panel F is a graph showing data with the S139N manifold. Dark-shaded bars indicate fluorescence measured when S139N-targeted crRNA is used in the detection reaction, and light-shaded bars indicate fluorescence measured when N139S-targeted crRNA is used. Error bars indicate 1SD for three technically identical samples.

Panel A is a schematic showing how the multi-serotype dengue SHERLOCK panel works. In panel B, each tick on the x-axis represents a g-block template that was used as input for the SHERLOCK reaction. Each shade of purple indicates a serotype-specific crRNA. Error bars indicate 1 SD for three technically identical samples. Panel C is another representation of the bars plotted in (b) as fluorescence on a log ₁₀ scale. Panel A is a schematic showing how the multi-serovar dengue SHERLOCK panel works. In panel B, each tick on the x-axis represents a g-block template that was used as input for the SHERLOCK reaction. Each shade of purple indicates a serotype-specific crRNA. Error bars indicate 1SD for three technically identical samples. Panel C is another representation of the bars plotted in (b) as fluorescence on a log ₁₀ scale.

Panel A is a schematic showing how the flavivirus SHERLOCK panel works. In panel B, each tick on the x-axis represents the g-block template used to input the SHERLOCK reaction. In panel C, each tick on the x-axis represents two g-block templates used as inputs for the SHERLOCK reaction to mimic the ability of SHERLOCK to detect co-infections. In alternating white and gray blocks, each bar is the fluorescence intensity obtained from guides tested in the order of ZIKV crRNA, WNV crRNA, DENV crRNA and YFV crRNA stored in each block. be. In panels B and C, each color indicates a virus-specific crRNA. Error bars indicate 1 SD for three technically identical samples. Panel A is a schematic showing how the flavivirus SHERLOCK panel works. In panel B, each tick on the x-axis represents the g-block template used to input the SHERLOCK reaction. In panel C, each tick on the x-axis represents two g-block templates used as inputs for the SHERLOCK reaction to mimic the ability of SHERLOCK to detect co-infections. In alternating white and gray blocks, each bar is the fluorescence intensity obtained from guides tested in the order of ZIKV crRNA, WNV crRNA, DENV crRNA and YFV crRNA stored in each block. be. In panels B and C, each color indicates a virus-specific crRNA. Error bars indicate 1 SD for three technically identical samples.

Panels A and B are alternative representations of the measured fluorescence shown in the bar graphs of Figures 80B and 80C, respectively. The slope is the log ₁₀ scale fluorescence after 3 hours.

Sensitive ZIKV detection from clinical samples and mosquito sources. (A) Schematic of SHERLOCK applied to clinical samples. Nucleic acids are extracted from clinical samples and target molecules are amplified by recombinase polymerase amplification (RPA). RNA samples are reverse transcribed (RT) prior to RPA. RPA products were detected (for in vitro transcription of dsDNA RPA products) using a reaction containing T7 RNA polymerase, purified Casl3a, crRNA, and an RNA reporter that fluoresces when cleaved. (B) SHERLOCK was tested on 40 samples collected during the 2016 ZIKV outbreak. The cDNA was SHERLOCKed with a 20 minute RPA reaction and 1 hour Cas13a detection. The dashed blue line indicates the threshold for the presence or absence of ZIKV (see Methods for details). (C) Comparison of SHERLOCK fluorescence and amplification product PCR yield. SHERLOCK and amplified product PCR were performed on the 40 ZIKV cDNA samples shown in (B). Amplification product PCR yield is the minimum concentration (ng/μL) of two separate amplification reactions using primer sources that tile the ZIKV genome (overlapping sequences). The dashed line indicates the threshold that determines the presence or absence of ZIKV. Blue is SHERLOCK, red is amplification product PCR. The Venn diagram shows the number of samples meeting these thresholds for each method. In some cases, data points nearly overlapped, indicated by numbers in parentheses. N. D. is "undetected".

Direct detection of ZIKV cDNA, RNA and particles from urine. (A) Detection of ZIKV cDNA diluted in untreated healthy human urine (red) using SHERLOCK. (B) Detection of ZIKV RNA diluted in untreated (red) or treated (blue) healthy human urine using SHERLOCK. (C) Detection of ZIKV particles diluted in PBS (gray) or untreated healthy human urine (red) using SHERLOCK. Undiluted virus stocks are shown in black. Three-hour fluorescence is shown for most diluted samples and no input (inset). In all panels, samples were treated with TCEP/EDTA and heated to inactivate both virus and RNase immediately after dilution. The length of heat treatment is indicated in the schematic. Error bars indicate 1 SD for three technically identical samples.

The SHERLOCK panel can distinguish virus species and serotypes. (A) Detection of four related flaviviruses using SHERLOCK. (B) Both a bar graph and a heat map show the target-specific fluorescence intensity after 3 h for each crRNA against each virus. (C) Target-specific fluorescence after 3 hours when two viral targets are present in one sample. (D) Detection of DENV serotypes 1-4 using SHERLOCK. (E) Target-specific fluorescence after 3 hours of serotype-specific crRNAs for each of the DENV serotypes. Target-specific fluorescence is the fluorescence for each target crRNA relative to the fluorescence for no input crRNA. In all panels, error bars indicate 1SD for 3 technically identical samples. The SHERLOCK panel can distinguish virus species and serotypes. (A) Detection of four related flaviviruses using SHERLOCK. (B) Both a bar graph and a heat map show the target-specific fluorescence intensity after 3 h for each crRNA against each virus. (C) Target-specific fluorescence after 3 hours when two viral targets are present in one sample. (D) Detection of DENV serotypes 1-4 using SHERLOCK. (E) Target-specific fluorescence after 3 hours of serotype-specific crRNAs for each of the DENV serotypes. Target-specific fluorescence is the fluorescence for each target crRNA relative to the fluorescence for no input crRNA. In all panels, error bars indicate 1SD for 3 technically identical samples. The SHERLOCK panel can distinguish virus species and serotypes. (A) Detection of four related flaviviruses using SHERLOCK. (B) Both a bar graph and a heat map show the target-specific fluorescence intensity after 3 h for each crRNA against each virus. (C) Target-specific fluorescence after 3 hours when two viral targets are present in one sample. (D) Detection of DENV serotypes 1-4 using SHERLOCK. (E) Target-specific fluorescence after 3 hours of serotype-specific crRNAs for each of the DENV serotypes. Target-specific fluorescence is the fluorescence for each target crRNA relative to the fluorescence for no input crRNA. In all panels, error bars indicate 1SD for 3 technically identical samples.

Identification of adaptive and functional ZIKV mutations from outbreaks. (A) Schematic showing how the SHERLOCK assay is designed for SNP identification. Light colors are used to indicate ancestral crRNAs and dark colors are used to indicate derived crRNAs. (B) SHERLOCK assay for three SNPs from the 2016 ZIKV outbreak. Applicants present a simplified phylogenetic tree describing the genomic location of each of the SNPs and their evolutionary relationships. (C) SNP identification test using synthetic targets. Fluorescence values for derived (dark) and ancestral (light) crRNA are shown for each of the three region-specific SNPs. (D) Identification of region-specific SNPs in samples from the 2016 ZIKV outbreak. Three SNP identification assays were used to evaluate cDNA samples from the Dominican Republic (DOM), the United States (USA), and Honduras (HND). Applicants present the fluorescence intensity ratio (derived crRNA fluorescence divided by ancestral crRNA fluorescence) for each SNP and each sample. (E) is a representation of the data in (D) transformed to log ₂ as a heat map. (F) Identification of ZIKV SNPs associated with microcephaly. (C) Similarly, dark color indicates derived crRNA and light color indicates ancestral crRNA. In all panels, error bars indicate 1SD for 3 technically identical samples. Identification of adaptive and functional ZIKV mutations from outbreaks. (A) Schematic showing how the SHERLOCK assay is designed for SNP identification. Light colors are used to indicate ancestral crRNAs and dark colors are used to indicate derived crRNAs. (B) SHERLOCK assay for three SNPs from the 2016 ZIKV outbreak. Applicants present a simplified phylogenetic tree describing the genomic location of each of the SNPs and their evolutionary relationships. (C) SNP identification test using synthetic targets. Fluorescence values for derived (dark) and ancestral (light) crRNA are shown for each of the three region-specific SNPs. (D) Identification of region-specific SNPs in samples from the 2016 ZIKV outbreak. Three SNP identification assays were used to evaluate cDNA samples from the Dominican Republic (DOM), the United States (USA), and Honduras (HND). Applicants present the fluorescence intensity ratio (derived crRNA fluorescence divided by ancestral crRNA fluorescence) for each SNP and each sample. (E) is a representation of the data in (D) transformed to log ₂ as a heat map. (F) Identification of ZIKV SNPs associated with microcephaly. (C) Similarly, dark color indicates derived crRNA and light color indicates ancestral crRNA. In all panels, error bars indicate 1SD for 3 technically identical samples.

SHERLOCK can detect ZIKV cDNA with high sensitivity. Applicants show SHERLOCK fluorescence values after 20 minutes of RPA and 1 hour of detection on serial dilutions of ZIKV cDNA. Error bars indicate 1 SD for three technically identical samples. In this experiment, RNase Alert v1 (IDT) was used as the RNA reporter.

(AD) SHERLOCK fluorescence data after 1 hour for 40 cDNA samples from the 2016 ZIKV outbreak. The sample name indicates the country of collection, the year of collection of the sample, the name of the sample, and the type of sample. Sample types are indicated as PLA: plasma sample, SER: serum sample, URI: urine sample, MOS: mosquito source. The countries of harvest are indicated by the abbreviations HND: Honduras, DOM: Dominican Republic, USA: USA. Error bars indicate 1 SD for three technically identical samples. The positive control (purple) shown in each plot is cultured virus seed stock (PE243). Negative controls are shown in orange. (AD) SHERLOCK fluorescence data after 1 hour for 40 cDNA samples from the 2016 ZIKV outbreak. The sample name indicates the country of collection, the year of collection of the sample, the name of the sample, and the type of sample. Sample types are indicated as PLA: plasma sample, SER: serum sample, URI: urine sample, MOS: mosquito source. The countries of harvest are indicated by the abbreviations HND: Honduras, DOM: Dominican Republic, USA: USA. Error bars indicate 1 SD for three technically identical samples. The positive control (purple) shown in each plot is cultured virus seed stock (PE243). Negative controls are shown in orange. (AD) SHERLOCK fluorescence data after 1 hour for 40 cDNA samples from the 2016 ZIKV outbreak. The sample name indicates the country of collection, the year of collection of the sample, the name of the sample, and the type of sample. Sample types are indicated as PLA: plasma sample, SER: serum sample, URI: urine sample, MOS: mosquito source. The countries of harvest are indicated by the abbreviations HND: Honduras, DOM: Dominican Republic, USA: USA. Error bars indicate 1 SD for three technically identical samples. The positive control (purple) shown in each plot is cultured virus seed stock (PE243). Negative controls are shown in orange. (AD) SHERLOCK fluorescence data after 1 hour for 40 cDNA samples from the 2016 ZIKV outbreak. The sample name indicates the country of collection, the year of collection of the sample, the name of the sample, and the type of sample. Sample types are indicated as PLA: plasma sample, SER: serum sample, URI: urine sample, MOS: mosquito source. The countries of harvest are indicated by the abbreviations HND: Honduras, DOM: Dominican Republic, USA: USA. Error bars indicate 1 SD for three technically identical samples. The positive control (purple) shown in each plot is cultured virus seed stock (PE243). Negative controls are shown in orange.

Amplification product PCR primer source data and thresholding. (A) Scatter plot of the respective ng/μL concentrations (measured on the Agilent tapestation) of the two amplicon PCR primer sources for each cDNA sample. In some cases the data points nearly overlapped and are indicated by the numbers in brackets. N. D. is "undetected". Positive controls (purple crosses) were cultured viral seed stocks (PE243) and negative controls (orange Xs) included 1 no input control and 4 healthy urine samples from 1 donor. (B) Scatterplot of amplification product PCR yield (ng/μl) versus genome coverage from recent Zika sequencing efforts (Metsky et al. 2017). The amplicon PCR yield is defined by the lowest amplicon DNA concentration (measured by Agilent tapestation) of the two amplicon PCR sources. Genomic coverage is normalized to 1. Technically identical samples of the sequencing library are shown in separate circles. (C) Applicants set _F0.5 statistics for varying thresholds for accuracy (true positives divided by the sum of true positives and false positives), recall (sensitivity), and amplification product PCR yield. show. The amplicon PCR yield threshold was chosen to maximize the F _0.5 statistic. Amplification product PCR primer source data and thresholding. (A) Scatter plot of the respective ng/μL concentrations (measured on the Agilent tapestation) of the two amplicon PCR primer sources for each cDNA sample. In some cases the data points nearly overlapped and are indicated by the numbers in brackets. N. D. is "undetected". Positive controls (purple crosses) were cultured viral seed stocks (PE243) and negative controls (orange Xs) included one no input control and four healthy urine samples from one donor. (B) Scatterplot of amplification product PCR yield (ng/μl) versus genome coverage from recent Zika sequencing efforts (Metsky et al. 2017). The amplicon PCR yield is defined by the lowest amplicon DNA concentration (measured by Agilent tapestation) of the two amplicon PCR sources. Genomic coverage is normalized to 1. Technically identical samples of the sequencing library are shown in separate circles. (C) Applicants set _F0.5 statistics for varying thresholds for accuracy (true positives divided by the sum of true positives and false positives), recall (sensitivity), and amplification product PCR yield. show. The amplicon PCR yield threshold was chosen to maximize the F _0.5 statistic. Amplification product PCR primer source data and thresholding. (A) Scatter plot of the respective ng/μL concentrations (measured on the Agilent tapestation) of the two amplicon PCR primer sources for each cDNA sample. In some cases the data points nearly overlapped and are indicated by the numbers in brackets. N. D. is "undetected". Positive controls (purple crosses) were cultured viral seed stocks (PE243) and negative controls (orange Xs) included one no input control and four healthy urine samples from one donor. (B) Scatterplot of amplification product PCR yield (ng/μl) versus genome coverage from recent Zika sequencing efforts (Metsky et al. 2017). The amplicon PCR yield is defined by the lowest amplicon DNA concentration (measured by Agilent tapestation) of the two amplicon PCR sources. Genomic coverage is normalized to 1. Technically identical samples of the sequencing library are shown in separate circles. (C) Applicants set _F0.5 statistics for varying thresholds for accuracy (true positives divided by the sum of true positives and false positives), recall (sensitivity), and amplification product PCR yield. show. The amplicon PCR yield threshold was chosen to maximize the F _0.5 statistic.

Inactivation of RNase using heat and chemical treatment. Serial 1:4 dilutions of RNase A (1 μg/ml) or healthy human urine were treated with TCEP and EDTA at final concentrations of 100 mM and 1 mM, respectively. Samples were incubated at 95° C. for 10 minutes, RNase Alert v1 (IDT) was added to each sample and fluorescence was monitored to determine nuclease activity. Fluorescence values after 1 hour incubation at 37° C. are shown. Error bars indicate 1 SD for three technically identical samples.

(A) Pretreatment of urine enables highly sensitive RNA detection with SHERLOCK. Applicants provided fluorescence data after 1 hour detection of RNA diluted in water (blue) and in urine (light red) pretreated with 100 mM TCEP and 1 mM EDTA for 10 minutes at 95°C. show. (B) Carrier RNA does not improve SHERLOCK sensitivity. Applicants diluted ZIKV RNA in healthy human urine that was partially inactivated in the presence or absence of 100 ng of carrier RNA (see Methods section for details). As in (A), 1 hour detection was used. Error bars indicate 1 SD for three technically identical samples. (A) Pretreatment of urine enables highly sensitive RNA detection with SHERLOCK. Applicants provided fluorescence data after 1 hour detection of RNA diluted in water (blue) and in urine (light red) pretreated with 100 mM TCEP and 1 mM EDTA for 10 minutes at 95°C. show. (B) Carrier RNA does not improve SHERLOCK sensitivity. Applicants diluted ZIKV RNA in healthy human urine that was partially inactivated in the presence or absence of 100 ng of carrier RNA (see Methods section for details). As in (A), 1 hour detection was used. Error bars indicate 1 SD for three technically identical samples.

RNase inactivation at low temperature. Applicants tested a two-step heat inactivation test protocol in which healthy human urine was incubated at 50°C for 20 minutes and then at 95°C for 5 minutes. After the 50°C step, the RNA was diluted in urine before the 95°C step. Error bars indicate 1 SD for three technically identical samples.

A panel showing the time course of flaviviruses. Each panel shows background-corrected fluorescence of virus-specific crRNA for each flavivirus target and no input control. Fluorescence shows a change over time over a period of 3 hours with fluorescence measurements taken every 5 minutes. Error bars indicate 1SD for three technically identical samples.

Time course of flavivirus co-infection. Panels Each panel shows background-corrected fluorescence of all crRNAs for samples containing two flavivirus targets. Fluorescence shows a change over time over a period of 3 hours with fluorescence measurements taken every 5 minutes. Each panel also contains the background-corrected fluorescence observed for each crRNA relative to no input controls. Error bars indicate 1 SD for three technically identical samples.

Dengue fever time course panel. Each panel shows background-corrected fluorescence of DENV serotype-specific crRNAs for all DENV serotypes and no input controls. Fluorescence shows a change over time over a period of 3 hours with fluorescence measurements taken every 5 minutes. Error bars indicate 1 SD for three technically identical samples.

SNP design planned. Applicants demonstrate the steps necessary to design, construct, and test a SNP identification assay with SHERLOCK. Total turnaround time is less than 1 week.

Identification of ZIKV microcephaly-associated SNPs by alternative crRNA designs. This SNP is at position 7 of the crRNA and there is no synthetic mismatch introduced into this crRNA. Dark colors indicate derived crRNAs, light colors indicate ancestral crRNAs. Error bars indicate 1 SD for three technically identical samples.

The SHERLOCK assay can identify six drug resistance mutations in HIV reverse transcriptase. Applicant presents the SNP identification index. This index is calculated by dividing the fluorescence intensity ratio of the progenitor template by the fluorescence intensity ratio of the progenitor template (see Methods section for details). This index is equal to 1 if there is no ability to discriminate between the ancestral and derived alleles, and the index is higher if the ability to discriminate between the two alleles is high. Error bars indicate 1 SD for three technically identical samples.

FIG. 1 shows that SHERLOCK can detect ZIKV cDNA with high sensitivity. SHERLOCK fluorescence values after 20 min RPA, 1 hour detection of serial dilutions of ZIKV cDNA are shown. A sensitivity of 0.9 aM corresponds to a 1 copy sensitivity where 2 aM = 1 cp/μl and 2 μl of sample was used as input. Error bars indicate 1 SD for three technically identical samples.

Detection of ZIKV and DENV from patient samples and clinical isolates. (A) Schematic of SHERLOCK. Nucleic acids are extracted from clinical samples and targets are amplified by RPA using either RNA or DNA (RT-RPA or RPA) as input. RPA products are detected in reactions containing T7 RNA polymerase, Cas13, target-specific crRNA, and an RNA reporter that fluoresces when cleaved. (B) cDNA from 37 patient samples collected during the 2015-2016 ZIKV outbreak and (C) from 16 patient samples compared head-to-head in the AltonaRealStar Zika virus RT-PCR assay. The cDNA was tested with SHERLOCK. +: ZIKV species stock solution cDNA (3×10 ² cp/μl), ×: no input. (D) SHERLOCK performed on RNA from 24 DENV-positive patient samples and clinical isolates. The dashed blue line is the threshold for the presence or absence of ZIKV or DENV (see Methods).

A comparison of SHERLOCK with other nucleic acid amplification tests is shown. Venn diagrams comparing (A) SHERLOCK and AltonaRealStar Zika virus RT-PCR assay results, (B) SHERLOCK and AltonaRealStar Zika virus RT-PCR assays, and Hologic Aptima Zika virus assay results.

Schematic representation of regions of the ZIKV genome targeted by SHERLOCK and other diagnostic methods. PCR amplicons tile the entire ZIKV genome, whereas the SHERLOCK ZIKV assay targets only one region of the ZIKV genome with short amplicons. The AltonaRealStar RT-PCR assay and the Hologic Aptima TMA assay also target individual short amplicons of the ZIKV genome (location and size of these amplicons are proprietary and not shown in the schematic). It is possible to have clinical samples that contain highly fragmented RNA (product length about 400 nt) that cannot be amplified by PCR primers. Conversely, it is possible to have a clinical sample containing a partial ZIKV genome that does not contain a SHERLOCK amplification product of about 120 nt.

FIG. 10 is a graph showing pan-dengue SHERLOCK detection limits for RNA derived from four DENV serotypes. (AD) SHERLOCK fluorescence values after 20 min RPA and 1 h detection on serial dilutions of DENV RNA from synthetic templates. 1 μl of sample was used as input. Error bars indicate 1 SD for three technically identical samples.

Pan Dengue SHERLOCK Pan Dengue SHERLOCK applied to patient samples and clinical isolates. (A) Pan-dengue SHERLOCK fluorescence of RNA extracted from 24 samples and 4 stocks indicated by DENV serotype. (BD) 14 human serum samples with 1 hour Cas13 detection (B), 10 cultured clinical isolates with 1 hour Cas13 detection (C), and 4 DENV species stocks with 1 hour Cas13 detection ( D) Pan-dengue SHERLOCK fluorescence of RNA extracted from.

Direct detection of ZIKV and DENV in body fluids by HUDSON and SHERLOCK. (A) Schematic of direct virus detection using HUDSON and SHERLOCK. (BC) Detection of ZIKV RNA in particles diluted in healthy human serum (pink, B) or healthy human saliva (blue, C). The same PBS controls as in A and B were used since the experiments were done together. (D) Detection of ZIKV RNA in particles diluted in healthy human urine (yellow). Black: undiluted virus stock. Gray: dilutions in PBS. Error bars indicate 1 SD for three technically identical samples. (EF) Detection of DENV RNA directly from patient serum (E) and saliva samples (F). (G) Lateral flow detection of DENV from samples shown in (EF). All samples were treated with TCEP/EDTA before heating.

Graph showing detection of ZIKV cDNA directly from blood products using SHERLOCK. ZIKV cDNA was diluted in healthy human whole blood (red), healthy human plasma (purple), healthy human serum (pink), or water (grey). Immediately after dilution, body fluids were treated with 100 mM TCEP and 1 mM EDTA at 50° C. for 5 minutes and then at 64° C. for 5 minutes. Error bars indicate 1 SD for three technically identical samples.

Graph showing detection of ZIKV cDNA directly from saliva using SHERLOCK. ZIKV cDNA was diluted in healthy human saliva (blue) or water (grey). Immediately after dilution, body fluids were treated with 100 mM TCEP and 1 mM EDTA at 50° C. for 5 minutes and then at 64° C. for 5 minutes. Error bars indicate 1SD for three technically identical samples.

Graph showing rapid inactivation of whole blood, plasma, and urine by RNAse. Healthy human whole blood, plasma, and urine were diluted as indicated and inactivated with 100 mM TCEP and 1 mM EDTA at 50° C. for 5 minutes. After incubation for 1 hour at 37° C., RNase activity was measured in the presence of 2 U/μl Murine RNase inhibitor (NEB) using RNase Alert v2 (Thermo). Two technically identical samples (orange and black bars) are shown for each condition.

Fig. 10 is a graph showing the detection of Zika virus diluted in whole blood. After 1 hour of detection, ZIKV RNA was detected in particles diluted in healthy human whole blood (red). Samples were heated with 100 mM TCEP and 1 mM EDTA at 50° C. for 5 minutes, then 64° C. for 5 minutes. The same PBS control as in Figures 104A and 104B was used since the experiments were done together. Error bars indicate 1 SD for three technically identical samples.

Fig. 3 is a graph showing the thermal inactivation of body fluids at body temperature; Healthy human whole blood, serum, saliva, and urine were diluted as indicated and inactivated with 100 mM TCEP and 1 mM EDTA for 20 minutes at 37°C. After incubation for 1 hour at 37° C., RNase activity was measured in the presence of 2 U/μl Murine RNase inhibitor (NEB) using RNase Alert v2 (Thermo). Two technically identical samples (orange and black bars) are shown for each condition.

FIG. 10 is a graph showing detection of dengue virus diluted in whole blood, serum, and saliva. One hour after detection, DENV RNA was detected in particles diluted in healthy human whole blood (red, A), serum (pink, B), or healthy human saliva (blue, C). Samples were heated at 37° C. for 20 min, 64° C. for 5 min and inactivated with 100 mM TCEP and 1 mM EDTA. The same PBS control was used in all panels because the experiments were done together. DENV titers are given in focus forming units per ml (FFU/ml). Error bars indicate 1SD for three technically identical samples.

2 shows a bar graph of dengue clinical sample RNA serotypes. (AD) From one DENV1 sample (A), two DENV2 samples and two samples with DENV2 and DENV3 present (B), four DENV3 samples (C), and three DENV4 samples (D). DENV panel by SHERLOCK distinguishing serotypes tested on extracted RNA. Fluorescence values 3 hours after Casl3 detection are shown. Error bars indicate 1SD for three technically identical samples.

Identification of adaptive and functional ZIKV mutations. (A) SHERLOCK assay for SNP identification. Dark: derived crRNA, light: ancestral crRNA. (B-C) Three region-specific SNPs from the 2015-2016 ZIKV outbreak, including the genomic location of the SNPs and a simplified phylogenetic tree. These SNPs were tested using synthetic targets (104 cp/μl) and viral seed stock cDNA (3×10 ² cp/μl). (DE) Identification of region-specific SNPs in ZIKV cDNA samples from the Dominican Republic (DOM), United States (USA), and Honduras (HND). Fluorescence ratios (derived crRNA fluorescence divided by ancestral crRNA fluorescence) for each SNP in each sample are shown in bar graphs (log ₂ transformed data in heatmap). (F) Schedule for developing SHERLOCK assays for novel SNPs (see Figure 113 for further details). (GH) Identification of the microcephaly-associated ZIKV mutation (PrM S139N) by fluorescence and colorimetric detection. In all panels, error bars indicate 1SD for 3 technically identical samples.

SNP design schedule is shown. Applicants demonstrate the steps necessary to design, construct, and test a SNP identification assay with SHERLOCK. Total turnaround time is less than 1 week.

Sidestream detection of Zika virus diluted in urine is shown by visual readout. Sidestream detection of Zika virus diluted in urine is shown (Fig. 104C). The top band is the test band and the bottom band is the control band. A weak band is visualized at 10 copies per microliter diluted in both PBS and urine after 1 hour of detection. [Detailed description of the invention] General definitions

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. Definitions of general and technical terms of molecular biology may be found in: Molecular Cloning: A Laboratory Manual, 2nd edition (1989) (Sambrook, Fritsch, and Maniatis); Molecular Cloning: A Laboratory Manual, 4th edition (2012) (Green and brook); Current Protocols in Molecular Biology (1987) (F.M. Ausubel et al. eds.); the series Methods in Enzymology (Academic Press, Inc.): PCR 2: A Practical Approach (1995) (M.J. MacPherson, B.D. Hames, and G.R. Taylor eds.): Antibodies, A Laboraotry Manual (1988) (Harlow and Lane, eds.): Antibodies A Laboraotry Manual, 2nd edition 2013 (E.A. Greenfield ed.); Animal Cell Culture (Animal cell culture) (1987) (R.I. Freshney, ed.); Benjamin Lewin, Genes IX, published by Jones and Bartlet, 2008 (ISBN 0763752223); Kendrew et al. (eds.), The Encyclopedia of Molecular Biology ( Molecular Biology Dictionary, published by Blackwell Science Ltd., 1994 (ISBN 0632021829); Robert A. Meyers (ed.), Molecular Biology and Biotechnology: a Comprehensive Desk Reference. ), published by VCH Publishers, Inc., 1995 (ISBN 9780471185710); Singleton et al., Dictionary of Microbiology and Molecular Biology 2nd ed., J. Wiley & Sons ( New York, N.Y. 1994), March, Advanced Organic Chemistry Reactions, Mechanisms and Structure 4th ed., John Wiley & Sons (New York, N.Y. 1992); and Marten H. Hofker and Jan van Deursen, Transgenic Mouse Methods and Protocols, 2nd edition (2011).

As used herein, the singular forms “a,” “an,” and “the” include both singular and plural referents unless the context clearly dictates otherwise.

The terms "optional" or "optionally" mean that the subsequently described event may or may not occur, and that the description includes whether or not the event or circumstance occurs.

The recitation of numerical ranges by endpoints includes all numbers and fractions subsumed within the respective range as well as the recited endpoints.

"About" or "approximately," as used herein, when describing a measurable value such as a parameter, amount, duration, etc., so long as the variation is appropriate to practice the disclosed invention. It is meant to include values and variations thereof, such as a stated value and values up to ±10%, up to ±5%, up to ±1%, and up to ±0.1% thereof. Obviously, values marked with the modifier "about" or "approximately" are preferably specifically disclosed.

References to "an aspect," "an embodiment," or "an exemplary embodiment" throughout this specification mean that the particular feature, structure, or characteristics described in connection with that embodiment are the present invention. It means that it is included in at least one aspect of. Thus, the phrases "in one aspect," "in one embodiment," or "an exemplary embodiment" used in various places throughout this specification do not necessarily all refer to the same embodiment at first glance. No, but sometimes it is. Moreover, it will be apparent to those skilled in the art from this disclosure that the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. Moreover, some embodiments described herein include some features that are included in other embodiments but not others, and combinations of features from different embodiments are within the scope of the invention. means that For example, in the appended claims any of the claimed embodiments may be used in any combination.

All publications, published patent documents and patent applications cited in this specification are hereby incorporated by reference to the same extent, although each individual publication, published patent document or patent application was specifically and separately indicated as being incorporated by reference.

Overview

The bacterial clustered short palindrome (CRISPR) and CRISPR-associated (CRISPR-Cas) adaptive immune system contains programmable endonucleases such as Cas9 and Cpf1 (Shmakov et al., 2017; Zetsche et al. 2015). Both Cas9 and Cpf1 target DNA, but recently single effector RNA-guided RNases (including C2c2) have been discovered (Shmakov et al., 2015) and characterized (Abudayyeh et al., 2015). al., 2016; Smargon et al., 2017), which provides a mechanism for sensing specific RNAs. RNA-guided RNases can be easily and conveniently reprogrammed with CRISPR RNA (crRNA) to cleave target RNAs. Unlike the DNA endonucleases Cas9 and Cpf1, which cleave only their DNA targets, RNA-guided RNases such as C2c2 remain active after cleaving their RNA targets, and are 'collateral' to nearby non-target RNAs. )” cleavage occurs (Abudayyeh et al., 2016). This crRNA-programmed secondary RNA-cleavage activity can act as a readout for specific RNA-cleavage activities using RNA-directed RNases by inducing programmed cell death in vivo or non-specific RNAs in vitro. It provides an opportunity to detect the presence of RNA (Abudayyeh et al., 2016; East-Seletsky et al., 2016).

Embodiments disclosed herein utilize RNA targeted effectors to provide robust diagnostics with CRISPR-based aM sensitivity. Embodiments disclosed herein can detect both DNA and RNA with equal sensitivity and can distinguish between targets and non-targets based on a single base pair difference. Embodiments disclosed herein may also be made in freeze-dried form for convenience of distribution and point-of-care (POC) applications. Such embodiments are useful in multiple contexts in human health, such as detection of viruses, classification of bacterial strains, sensitive genotyping, and detection of cell-free DNA associated with disease.

Rapid, sensitive, low-cost, user-friendly, and rapidly adaptable assays for the detection of newly identified agents are needed to diagnose infectious organisms worldwide. Embodiments disclosed herein demonstrate that the Cas 13 based SHERLOCK device is capable of detecting Zika virus (ZIKV) in clinical samples and mosquito sources with single copy sensitivity and can detect ZIKV directly from urine in less than 2 hours. Indicates that it can be detected. Applicants have further developed an assay that simultaneously detects four flaviviruses, an assay that distinguishes between dengue virus serotypes 1-4, and a region-specific variant of the ZIKV derived from the 2016 pandemic. developed an assay to distinguish between strains of Finally, Applicants developed and tested an assay that identified ZIKV variants associated with fetal microcephaly within one week of its publication. The results show that SHERLOCK can detect viruses originating directly from bodily fluids, distinguish between multiple pathogenic viruses, and can be rapidly updated to identify mutations associated with clinically relevant phenotypes. .

In one aspect, embodiments disclosed herein amplify a CRISPR system, one or more guide RNAs designed to bind to corresponding target molecules, a masking construct, and a target nucleic acid molecule in a sample. It relates to a nucleic acid detection system containing any amplification reagents. In certain exemplary embodiments, the system may further comprise one or more detection aptamers. The one or more detection aptamers may contain an RNA polymerase site or a primer binding site. The one or more detection aptamers are configured to specifically bind to one or more target polypeptides such that the RNA polymerase site or primer binding site is exposed only when the detection aptamer binds to the target peptide. ing. The exposure of the RNA polymerase site facilitates the generation of trigger RNA oligonucleotides using the aptamer sequence as a template. Accordingly, in such embodiments, said one or more guide RNAs are configured to bind to one trigger RNA.

In another aspect, embodiments disclosed herein relate to a diagnostic device that includes multiple discrete volumes. Each separate volume contains a CRISPR effector protein, one or more guide RNAs designed to bind to the corresponding target molecule, and a masking construct. In certain exemplary embodiments, said discrete volumes may be pre-filled with RNA amplification reagents, or said one or more discrete volumes may be filled into discrete volumes at the same time as or after addition of sample to each. You can add The device may be a microfluidic device, a wearable device, or a device comprising a matrix of flexible material in which the discrete volumes are defined.

In other aspects, embodiments disclosed herein relate to a method of detecting a target nucleic acid in a sample comprising dispensing a sample or set of samples into a set of discrete volumes. Each of the one or more individual volumes contains a CRISPR effector protein, one or more guide RNAs designed to bind to one target oligonucleotide, and a masking construct. The set of samples is then maintained under conditions sufficient to allow the one or more guide RNAs to bind to the one or more target molecules. Binding of the one or more guide RNAs to the target nucleic acid then activates the CRISPR effector protein. Once activated, the CRISPR effector protein inactivates the masking construct, e.g., by cleaving the masking construct to mask a detectable positive signal, or to release or generate a detectable positive signal. be done. Detection of a detectable positive signal in one discrete volume indicates the presence of said target molecule.

In yet another aspect, embodiments disclosed herein relate to methods of detecting a polypeptide. Methods for detecting the polypeptide are similar to the methods for detecting target nucleic acids described above. However, peptide detection aptamers are also included. The peptide detection aptamers function as described above to facilitate generation of trigger oligonucleotides upon binding to a target polypeptide. The guide RNA is designed to recognize a trigger oligonucleotide, thereby activating the CRISPR effector protein. Upon inactivation of the masking construct by an activated CRISPR effector protein, a detectable positive signal is masked or a detectable positive signal is released or produced.

CRISPR effector protein

Generally, the term “CRISPR-Cas or CRISPR system” as used herein and in literature such as WO2014/093622 (PCT/US2013/074667) refers to the expression of CRISPR-associated (“Cas”) genes involved in or directed to their activity. Collectively the transcripts and other elements that are Such include sequences encoding the Cas gene, transactivating (tracrCRISPR) sequences (e.g., tracrRNA or active portion tracrRNA), tracr mate sequences ("tandem repeats" in the context of the endogenous CRISPR system and tracrRNA processing ), a guide sequence (“spacer” in the context of the endogenous CRISPR system), or “RNA” as the term is used herein (e.g. RNA that guides Cas (Cas9, e.g. CRISPR RNA and trans-activating (tracr) RNA or single-stranded guide RNA (sgRNA) (chimeric RNA), or other sequences and transcripts derived from the CRISPR loci. (also referred to as a protospacer in the context of the endogenous CRISPR system) that promotes the formation of the CRISPR complex at the site of the tracrRNA is not required if the CRISPR protein is the C2c2 protein, C2c2 is described below. and is incorporated herein by reference in its entirety: Abudayyeh et al. (2016) "C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector." Science; DOI: 10.1126/science.aaf5573; and Shmakov et al. (2015) “Discovery and Functional Characterization of Diverse Class 2 CRISPR-Cas Systems”; Discovery and Functional Characterization”, Molecular Cell, DOI: dx.doi.org/10.1016/j.molcel.2015.10.008. -Associated RNA-Guided RNases Differentially Regulated by Accessory Proteins Csx27 and Csx28 -13; dx.doi.org/10.1016/j.molcel.2016.12.023, the entire contents of which are incorporated herein by reference.

In a particular aspect, the protospacer adjacent motif (PAM) or PAM-like motif relates to the binding of the effector protein complexes disclosed herein to the target locus of interest. In some variations, the PAM may be a 5'-PAM (ie, may be located upstream of the 5' end of the protospacer). In other embodiments, the PAM may be a 3'-PAM (ie, located downstream of the 5' end of the protospacer). The term "PAM" is sometimes interchangeable with the term "PFS (protospacer flanking site or protospacer flanking sequence) = protospacer binding sequence".

In one preferred aspect, the CRISPR effector protein may recognize 3'-PAM. In certain aspects, the CRISPR effector protein may recognize a 3'-PAM that is 5'H (where H is A, C, or U). In a particular embodiment, the effector protein may be Leptotrichia shaii C2c2p, more preferably Leptotrichia shaii DSM 19757 C2c2, and the 3'-PAM is 5'H.

In the context of CRISPR complex formation, "target sequence" refers to a sequence designed to be complementary to a guide sequence. Here, hybridization of the target and guide sequences facilitates formation of the CRISPR complex. A target sequence may comprise an RNA polynucleotide. The term "target RNA" refers to an RNA polynucleotide that is or contains a target sequence. In other words, the target RNA is a portion of the gRNA, i.e., the RNA polynucleotide or RNA polynucleotide to which the gRNA-mediated effector function is directed, a complex containing the CRISPR effector protein designed to have complementarity with the guide sequence. It may be part of a nucleotide. In some embodiments, the target sequence is located in the nucleus or cytoplasm of the cell.

A nucleic acid molecule encoding a CRISPR effector protein, in particular C2c2, is preferably an optimized CRISPR effector protein. In this case, an example of a codon-optimized sequence is, for example, a sequence optimized for expression in eukaryotes such as humans (i.e., optimized for human expression), or other sequences described herein. Sequences optimized for eukaryotic, animal, or mammalian expression. See, eg, SaCas9 human codon-optimized sequences in WO2014/093622 (PCT/US2013/074667). While this is preferred, as is self-evident, other examples are possible, codon-optimized for host species other than humans or codon-optimized for specific organs are known. In some embodiments, the enzyme coding sequence that encodes the CRISPR effector protein is codon optimized, particularly for expression in cells such as eukaryotic cells. Eukaryotic cells may be derived from a particular organism, such as a plant or a mammal, including but not limited to humans, non-human eukaryotes as described herein, animals, or mammals (e.g., mice, rats, rabbits, dogs, livestock), or non-human mammals or primates. In some embodiments, modifying human germline genetic identity and/or afflicting humans or animals, and animals obtained from such methods, without any substantial medical benefit. Methods that modify the genetic identity of an animal suspected to be may be excluded. Generally, codon optimization is performed by using at least one codon of the native sequence (e.g., about 1, 2, 3, 4, 5, 10, 15, 20, 25, 50, or more codons) with those codons used frequently or most frequently by the genes of the host cell while maintaining the native amino acid sequence, thereby modifying a nucleic acid sequence for enhanced expression in a host cell of interest. say. Different species exhibit particular biases for particular codons of particular amino acids. Codon bias (differences in codon usage between organisms) is often correlated with the efficiency of messenger RNA (mRNA) translation. This translation efficiency is thought to depend, among other things, on the properties of the codons being translated and the availability of the particular transfer RNA (tRNA) molecule. In general, the significance of a chosen tRNA within a cell is a reflection of the codons most frequently used in peptide synthesis. Thus, genes may be adjusted for optimal gene expression in a given organism based on codon optimization. Codon usage tables are readily available, for example, at "Codon Usage Database" (kazusa.orjp/codon/). These tables may be adapted in various ways. See Nakamura, Y., et al. "Codon usage tabulated from the international DNA sequence databases: status for the year 2000" Nucl. Acids Res. 28:292 (2000). Computer algorithms for codon optimization of a particular sequence for expression in a particular host cell are also available, such as Gene Forge (Aptagen, Jacobus, Pa.). In some embodiments, one or more codons (e.g., 1, 2, 3, 4, 5, 10, 15, 20, 25, 50, or more) are used in the Cas-encoding sequence. These codons, or all codons) correspond to the most frequently used codons for a particular amino acid.

In certain aspects, the methods described herein may comprise providing Cas-transgenic cells, particularly C2c2-transgenic cells. Here, one or more nucleic acids encoding one or more guide RNAs are provided or introduced to operatively bind to the cell by means of regulatory elements, including promoters of one or more genes of interest. As used herein, the term "Cas-transfected cell" refers to a cell, such as a eukaryotic cell, into which a Cas gene has been genomically integrated. The nature, type, or origin of the cells is not particularly limited by the present invention. Also, the method by which the Cas gene transfer is introduced into the cell may vary and may be any method known in the art. In certain aspects, Cas-transfected cells are obtained by introducing a Cas transgene into an isolated cell. In certain other embodiments, Cas-transgenic cells are obtained by isolating cells from a Cas-transgenic organism. By way of example, and not limitation, a Cas-transgenic cell as referred to herein may be derived from a Cas-transgenic eukaryote, such as a Cas knock-in eukaryote. See WO2014/093622 (PCT/US13/74667). The contents of which are incorporated herein by reference. The methods of US Patent Publication Nos. 20120017290 and 20110265198 directed to targeting the Rosa locus to Sangamo BioSciences may be modified to use the CRISPR-Cas system of the present invention. To take advantage of the CRISPR-Cas system of the present invention, the method of US Patent Publication No. 20130236946 to Cellectis for targeting the Rosa locus may be modified. For further examples, see Platt et. al. (Cell; 159(2):440-455 (2014)). This article describes Cas9 knock-in mice, the contents of which are incorporated herein by reference. The Cas transgene may further contain a Lox-Stop-polyA-Lox (LSL) cassette, which makes Cas expression inducible by Cre recombinase. Alternatively, Cas-transfected cells may be obtained by introducing a Cas transgene into isolated cells. Transgene delivery systems are well known in the art. By way of example, delivery of Cas transgenes into eukaryotic cells, e.g., by vector (e.g., AAV, adenovirus, lentivirus) and/or particle and/or nanoparticle delivery, as described elsewhere herein You may

As will be apparent to those skilled in the art, the cells referred to herein, such as Cas-transfected cells, in addition to having an integrated Cas gene, have additional genomic alterations or RNA It may further contain mutations resulting from sequence-specific effects of Cas upon binding to.

In certain aspects, the present invention provides, for example, delivery or introduction of Cas and/or RNA capable of directing Cas to a target locus (i.e., guide RNA) into cells while propagating these components (e.g., in prokaryotic cells). contains a vector that As used herein, the term "vector" is a tool that enables or facilitates the transfer of an entity from one environment to another. A vector is a replicon (unit of DNA replication), such as a plasmid, phage, or cosmid, into which other segments of DNA may be inserted and the inserted segments replicate. In general, vectors are capable of replication when associated with appropriate regulatory elements. In general, the term "vector" refers to a nucleic acid molecule capable of transporting other nucleic acids to which it has been linked. Vectors include, but are not limited to, nucleic acid molecules that are single-stranded, double-stranded, or partially double-stranded; nucleic acid molecules that contain one or more free ends; nucleic acids that lack free ends (e.g., circular) Nucleic acid molecules, including molecules, DNA, RNA, or both, and other polynucleotide variants known in the art. One type of vector is a "plasmid". Plasmid refers to a circular double-stranded DNA loop into which additional DNA segments can be inserted by standard molecular cloning techniques. Another type of vector is a viral vector. In this class, virus-derived DNA or RNA sequences are used for inclusion in viruses (e.g., retroviruses, replication-defective retroviruses, adenoviruses, replication-defective adenoviruses, and adeno-associated viruses (AAVs)). exist. Viral vectors also include a virally-carried polynucleotide for transfection into a host cell. Certain vectors (eg, bacterial vectors having a bacterial origin of replication and episomal mammalian vectors) are capable of autonomous replication in a host cell into which they are introduced. Other vectors (eg, non-episomal mammalian vectors) integrate into the host cell's genome upon introduction into the host cell, thereby replicating along with the host genome. In addition, certain vectors are capable of directing the expression of genes to which they are operatively linked. Such vectors are referred to herein as "expression vectors". Expression vectors commonly used in recombinant DNA techniques are often in the form of plasmids.

A recombinant expression vector may contain the nucleic acid of the invention in a form suitable for expression of the nucleic acid. This means that the recombinant expression vector contains one or more regulatory elements. The regulatory elements may be selected based on the host cell used for expression. The regulatory elements are operably linked to the nucleic acid sequences to be expressed. Within a recombinant expression vector, "operably linked" means that a nucleotide sequence is expressed (e.g., in an in vitro translation system, or in a host cell if the vector is introduced into a host cell) such that the nucleotide sequence of interest is expressed. It means attached to a regulatory element. Recombination and cloning methods are described in US patent application Ser. incorporated. Accordingly, embodiments disclosed herein may also include transgenic cells comprising a CRISPR effector system. In certain exemplary embodiments, transgenic cells may function as separate volumes. In other words, samples containing masking constructs may be delivered to cells, eg, suitable delivery vesicles. If the target is present in the delivery vesicle, the CRISPR effector is activated and a detectable signal is produced.

The vector may, for example, contain regulatory elements such as promoters. The vector may contain a Cas coding sequence and/or a single or possibly at least 3, 8, 16, 32, 48, or 50 guide RNAs (e.g., sgRNAs) coding sequences, such as 1-2, 1-3, 1-4, 1-5, 3-6, 3-7, 3-8, 3-9, 3-10, 3 It may contain ˜8, 3-16, 3-30, 3-32, 3-48, 3-50 RNAs (eg, sgRNAs). A single vector advantageously has one promoter for each RNA (eg, sgRNA) for up to about 16 RNAs. Where a single vector provides 17 or more RNAs, one or more promoters may drive expression of two or more of those RNAs. For example, if there are 32 RNAs, each promoter may drive expression of 2 RNAs, and if there are 48 RNAs, each promoter may drive expression of 3 RNAs. One of ordinary skill in the art can use simple arithmetic, well-established cloning protocols and the teachings of the present disclosure to construct the present invention as RNA for a suitable exemplary vector (e.g., AAV) and a suitable promoter (U6 promoter). can be easily implemented. For example, the inclusion limit for AAV is approximately 4.7 kb. The length of a single U6-gRNA (+restriction site for cloning) is 361 bp. Thus, one skilled in the art can easily fit about 12-16, eg, 13, U6-gRNA cassettes into a single vector. This can be assembled by any suitable means, such as the Golden Gate method used for TALE assembly (genome-engineering.org/taleffectors/). Alternatively, one skilled in the art can use the tandem guide method to increase the number of U6-gRNAs by about 1.5 fold, such as 12-16, such as 13 to about 18-24, such as about 19. U6-gRNA can be increased. Accordingly, one skilled in the art can easily achieve about 18-24, eg, about 19 promoter RNAs (eg, U6-gRNA) in a single vector (eg, AAV vector). A further means of increasing the number of promoters and RNAs in one vector is to use a single promoter (eg, U6) to express RNA arrays separated by cleavable sequences. A further means of increasing the number of promoter RNAs in a single vector is to express promoter RNA arrays separated into cleavable sequences at the coding sequences or introns of genes. In this case the use of the polymerase II promoter is beneficial. Polymerase II promoters can increase expression and transcribe long RNAs in a tissue-specific manner (e.g. nar.oxfordjournals.org/content/34/7/e53.short and nature.com/mt/ journal/v16/n9/abs/mt2008144a.html). In one preferred embodiment, AAV may include U6 tandem gRNAs targeting up to 50 genes. Therefore, given the knowledge in the art and the teachings of the present disclosure, one of ordinary skill in the art would, without undue experimentation, particularly with the number of RNAs or guides described herein, to A vector (eg, a single vector) expressing multiple RNAs or guides under the control of a promoter or operably or functionally linked thereto can be readily constructed and used.

The guide RNA coding sequence and/or Cas coding sequence may be functionally or operationally linked to a regulatory element whereby the regulatory element drives expression. The promoter may be a constitutive promoter and/or a conditional promoter and/or an inducible promoter and/or a tissue specific promoter. Promoters include RNA polymerase, pol I, pol II, pol III, T7, U6, H1, retrovirus Rous sarcoma virus (RSV) LTR promoter, cytomegalovirus (CMV) promoter, SV40 promoter, dihydrofolate reductase promoter, It may be selected from the group consisting of β-actin promoter, phosphoglycerin kinase (PGK) promoter, and EF1α promoter. A useful promoter is promoter U6.

In some embodiments, one or more elements of the nucleic acid targeting system are derived from a particular organism, including an endogenous CRISPR RNA targeting system. In certain exemplary embodiments, the effector protein CRISPR RNA targeting system comprises at least one HEPN domain. Such include, but are not limited to, HEPN domains described herein, HEPN domains known in the art, and domains recognized as HEPN domains compared to consensus sequence motifs. . Several such domains are provided herein. In one non-limiting example, the consensus sequence may be derived from the sequences of the C2c2 or Casl3b orthologues provided herein. In certain exemplary embodiments, the effector protein comprises a single HEPN domain. In certain other exemplary embodiments, the effector protein comprises two HEPN domains.

In one exemplary embodiment, the effector protein comprises one or more HEPN domains comprising RxxxxH motif sequences. Without limitation, the RxxxxH motif sequence may be derived from HEPN domains described herein or HEPN domains known in the art. RxxxxH motif sequences further include motif sequences made by combining portions of two or more HEPN domains. It should be noted that the consensus sequences may be derived from the sequences of the orthologs disclosed in: US Provisional Patent Application No. 62/432, entitled "Novel CRISPR Enzymes and Systems." , No. 240, U.S. Provisional Patent Application No. 62/471,710, filed March 15, 2017, entitled "Novel Type VI CRISPR Orthologs and Systems"; and U.S. Provisional Patent Application entitled "Novel Type VI CRISPR Orthologs and Systems" filed on April 12, 2017 (Attorney Docket No. 47627-05-2133). .

In one embodiment of the invention, the HEPN domain comprises at least one RxxxxH motif comprising the sequence R{N/H/K}X1X2X3H. In one embodiment of the invention, the HEPN domain comprises a RxxxxH motif comprising the sequence R{N/H}X1X2X3H. In one embodiment of the invention, the HEPN domain comprises the sequence R{N/K}X1X2X3H. In certain aspects, X1 is R, S, D, E, Q, N, G, Y, or H. In certain aspects, X2 is I, S, T, V, or L. In certain aspects, X3 is L, F, N, Y, V, I, S, D, E, or A.

Additional effectors for use according to the invention may be identified by their proximity to the cas1 gene, such as, but not limited to, within a region 20 kb from the beginning of the cas1 gene and 20 kb from the end of the cas1 gene. . In certain aspects, the effector protein comprises at least one HEPN domain and at least 500 amino acids, and the C2c2 effector protein is naturally occurring within 20 kb upstream or downstream of the Cas gene or CRISPR sequence of the prokaryotic genome. Non-limiting examples of Cas proteins include Cas1, Cas1B, Cas2, Cas3, Cas4, Cas5, Cas6, Cas7, Cas8, Cas9 (also known as Csn1 and Csx12), Cas10, Csy1, Csy2, Csy3, Cse1, Cse2, Csc1, Csc2, Csa5, Csn2, Csm2, Csm3, Csm4, Csm5, Csm6, Cmr1, Cmr3, Cmr4, Cmr5, Cmr6, Csb1, Csb2, Csb3, Csx17, Csx14, Csx10, Csx16, CsaX, Csx3 Csx1, Csx15, Csf1, Csf2, Csf3, Csf4, homologues or modified versions thereof. In certain exemplary embodiments, the C2c2 effector protein is naturally present within 20 kb upstream or downstream of the Cas1 gene of the prokaryotic genome. The terms "orthologue" (also referred to herein as "ortholog") and "homologue" (also referred to herein as "homologue") are well known in the art. By way of further guidance, a "homologue" of a protein, as used herein, is a homologous protein that performs the same or similar function as the protein to which it is a homologue. Homologous proteins may or may not be structurally related, but only partially structurally related. A "orthologue" of a protein is a protein of a different species that performs the same or similar function as the protein to which it is an orthologue. Homologous species proteins may be structurally related, unrelated, or only partially related structurally.

In certain embodiments, the Type VI RNA-targeted Cas enzyme is C2c2. In another exemplary embodiment, the Type VI RNA-targeted Cas enzyme is Casl3b. In certain embodiments, the homologue or orthologue of the C2c2 type VI protein referred to herein is C2c2 (e.g., Leptotorichia shaiii C2c2, Lachnospiraceae bacterium MA2020 C2c2, Lachnospiraceae bacterium NK4A179 C2c2, Clostridium aminophyllum (DSM 10710) C2c2, Carnobacterium gallinarum (DSM 4847) C2c2, Pardibacter propionisigenes (WB4) C2c2, Listeria weihenstephanensis (FSL R9-0317) C2c2, Listeriaceae (FSL M6-0635 ) C2c2, Listeria newyokensis (FSL M6-0635) C2c2, Leptotrichia weedii (F0279) C2c2, Rhodobacter capsulata (SB 1003) C2c2, Rhodobacter capsulata (R121) C2c2, Rhodobacter capsulata (DE442) C2c2, Leptotrichia at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80% of the type VI protein of Weidi (Lw2) C2c2, or any of Listeria ciligeri C2c2 based on the wild-type sequence , more preferably at least 85%, even more preferably at least 90%, such as at least 95% sequence homology or identity. In further embodiments, the homologue or orthologue of a type VI protein such as C2c2 referred to herein is a wild-type C2c2 (e.g., Leptotorichia shaiii C2c2, Lachnospiraceae MA2020 C2c2, Lachnospiraceae NK4A179 C2c2, Clostridium Aminophyllum (DSM 10710) C2c2, Carnobacterium gallinarum (DSM 4847) C2c2, Pardibacter propionisigenes (WB4) C2c2, Listeria weihenstephanensis (FSL R9-0317) C2c2, Listeriaceae bacteria ( FSL M6-0635) C2c2, Listeria newyokensis (FSL M6-0635) C2c2, Leptotorichia weedii (F0279) C2c2, Rhodobacter capsulata (SB 1003) C2c2, Rhodobacter capsulata (R121) C2c2, Rhodobacter capsulata (DE442) ) C2c2, Leptotorichia weedii (Lw2) C2c2, or Listeria seeligeri C2c2) and at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80% , more preferably at least 85%, even more preferably at least 90%, such as at least 95% sequence identity.

In certain other exemplary embodiments, the CRISPR system effector protein is a C2c2 nuclease. The activity of C2c2 may depend on the presence of two HEPN domains. These have been shown to be RNase domains, ie nuclease (especially endonuclease) cleaved RNAs. HEPN of C2c2 may also target DNA, possibly DNA and/or RNA. Based on the ability of the HEPN domain of C2c2 to bind at least RNA and cleave it in its wild-type form, the C2c2 effector protein preferably has RNase function. For the C2c2 CRISPR system, US Provisional Patent Application No. 62/351,662 filed June 17, 2016 and US Provisional Patent Application No. 62/376,377 filed August 17, 2016 checking ... See also U.S. Provisional Patent Application No. 62/351,803, filed Jun. 17, 2016. See also U.S. Provisional Patent Application entitled "Novel Crispr Enzymes and Systems" filed Dec. 8, 2016 (Broad Institute No. 10035.PA4 and Attorney Docket No. 47627.03. 2133). Furthermore, East-Seletsky et al. “Two distinct RNase activities of CRISPR-C2c2 enable guide-RNA processing and RNA detection” Nature doi:10/1038/nature19802 and Abudayyeh et al. "C2c2 is a single-component programmable RNA-guided RNA targeting CRISPR effector." bioRxiv doi: See 10.1101/054742.

The RNase function of the CRISPR system is known, for example mRNA targets have been reported in certain type III CRISPR-Cas systems (Hale et al., 2014, Genes Dev, vol. 28, 2432-2443; Hale et al., 2009, Cell, vol. 139, 945-956; Peng et al., 2015, Nucleic acids research, vol. 43, 406-417), yielding great utility. In the Staphylococcus epidermis type III-A system, target-spanning transcription cleaves the target DNA and its transcripts. This cleavage is mediated by an independent active site within the Cas10-Csm ribonucleoprotein effector protein complex (see Samai et al., 2015, Cell, vol. 151, 1164-1174). Accordingly, CRISPR-Cas systems, compositions, or methods for targeting RNA by effector proteins of the invention are provided.

In one embodiment, the Cas protein includes, but is not limited to, Leptotrichia, Listeria, Corynebacter, Satterella, Legionella, Treponema, Filifactor, Eubacterium, Streptococcus, Lactobacillus, Mycoplasma, Bacteroides, Flaviibora, Flavobacterium, Spherocheta , Azospirillum, Gluconacetobacter, Neisseria, Rosebria, Parvivacrum, Staphylococcus, Nitratifructor, Mycoplasma, and Campylobacter. Species of such genera may be those described herein.

Some methods of identifying orthologues of CRISPR-Cas system enzymes may include identifying tracr sequences in the subject's genome. Identification of tracr sequences may involve the following steps of searching databases for direct repeats or tracr mate sequences to identify CRISPR regions containing CRISPR enzymes. Homologous sequences in the CRISPR region flanking the CRISPR enzyme are searched in both sense and antisense strand orientations. Examine transcription terminators and secondary structure. Any sequence that is not a direct repeat or tracr mate sequence but has greater than 50% identity with a direct repeat or tracr mate sequence is identified as a potential tracr sequence. A potential tracr sequence is picked and analyzed for its associated transcription terminator sequence.

Obviously, any of the functions described herein can be engineered into CRISPR enzymes from other orthologues (including chimeric enzymes containing fragments from more than one orthologue). good too. Examples of such orthologues are described elsewhere herein. Thus, chimeric enzymes include, but are not limited to, Leptotrichia, Listeria, Corynebacter, Satterella, Legionella, Treponema, Filifactor, Eubacterium, Streptococcus, Lactobacillus, Mycoplasma, Bacteroides, Flaviibora, Flavobacterium, Sphaerocheta, Azospirillum, Fragments of CRISPR enzyme orthologs of organisms including Gluconacetobacter, Neisseria, Rosebria, Parvivacrum, Staphylococcus, Nitratiflactor, Mycoplasma, and Campylobacter may also be included. A chimeric enzyme may comprise a first fragment and a second fragment, which fragments may be CRISPR enzyme orthologues of organisms of the genus or species described herein. Preferably, these fragments are derived from different species of CRISPR enzyme orthologues.

In some embodiments, the C2c2 proteins referred to herein also include functional variants of C2c2, or homologues or orthologues thereof. As used herein, a "functional variant" of a protein refers to variants of that protein that at least partially retain the activity of the protein. Functional variants may include variants (which may be insertional, deletional or substitutional variants), including polymorphisms. Functional variants also include fusion products of such proteins with another, normally unrelated nucleic acid, protein, polypeptide, or peptide. A functional variant may be naturally occurring or man-made. Preferred embodiments may include engineered, ie, non-naturally occurring Type VI RNA target effector proteins.

In one embodiment, one or more nucleic acid molecules encoding C2c2 or orthologues or homologues thereof may be codon-optimized for expression in eukaryotic cells. The eukaryote may be as described herein. One or more of the nucleic acid molecules may be engineered, ie non-naturally occurring.

In one embodiment, C2c2 or its orthologs or homologues may comprise one or more mutations (and thus the nucleic acid molecule or nucleic acid molecules encoding it may have mutations). . These mutations may be artificially introduced mutations and may include, but are not limited to, one or more mutations in the catalytic domain. Examples of catalytic domains for Cas9 enzymes include, but are not limited to, RuvC I domain, RuvC II domain, RuvC III domain, and HNH domain.

In one embodiment, C2c2 or its orthologues or homologues may contain one or more mutations. These mutations may be artificially introduced mutations and may include, but are not limited to, one or more mutations in the catalytic domain. Examples of catalytic domains for Cas enzymes may include, but are not limited to, HEPN domains.

In one embodiment, C2c2 or its orthologues or homologues may be used as a universal nucleic acid binding protein fused or engineered to a functional domain. Examples of functional domains include, but are not limited to, translation initiators, translation activators, translation repressors, nucleases, especially ribonucleases, spliceosomes, beads, light-inducible/regulatory domains, or chemically-inducible/ It may also contain a regulatory domain.

In certain exemplary embodiments, the C2c2 effector protein is Leptotrichia, Listeria, Corynebacter, Satterella, Legionella, Treponema, Filifactor, Eubacterium, Streptococcus, Lactobacillus, Mycoplasma, Bacteroidetes, Flaviibola, Flavobacterium, Sphaerocheta, It may be derived from an organism selected from the group consisting of Azospirillum, Gluconacetobacter, Neisseria, Rosebria, Parvivacrum, Staphylococcus, Nitratifructor, Mycoplasma, and Campylobacter.

In a particular aspect, the effector protein may be a Listeria C2c2p species, preferably Listeria seeligeri C2c2p, more preferably Listeria seeligeri serovar 1/2b strain. The SLCC3954 C2c2p and crRNA sequences may be 44-47 nucleotides in length, with a 29 nt 5' terminal direct repeat (DR) and a 15-18 nt spacer.

In a particular aspect, the effector protein may be a Leptotrichia C2c2p species, preferably Leptotrichia shaii C2c2p, more preferably Leptotrichia shaii DSM 19757 C2c2p. Alternatively, the crRNA sequence may be 42-58 nucleotides in length and comprises at least 24 nt of 5′-terminal direct repeats, such as 24-28 nt of 5′-terminal direct repeats (DR) and at least 14 nt of spacers. , such as 14 nt to 28 nt, or at least 18 nt, such as 19, 20, 21, 22 nt, or more, such as 18 to 28, 19 to 28, 20 to 28, 21 to 28, or 22 to 28 nt. have.

In certain exemplary embodiments, the effector protein may be Leptotrichia, Leptotrichia weedii F0279, or Listeria, preferably Listeria newyokensis FSL M6-0635.

In certain exemplary embodiments, the C2c2 effector proteins of the invention include, but are not limited to, the following 21 orthologues (comprising multiple CRISPR loci): Leptotrichia shaii; Leptotrichia weidii (Lw2). Lachnospiraceae MA2020; Lachnospiraceae NK4A179; [Clostridium] Aminophyllum DSM 10710; Carnobacterium gallinarum DSM 4847; Pionisigenes WB4; Listeria weihenstephanensis FSL R9-0317; Listeriaceae FSL M6-0635; [Eubacterium] rectale; Eubacteriaceae CHKCI004; Brautia marseille sp. P2398; and Leptotorichia oral taxon sp. Chloroflexus agregans; Demechina aurantiaca; Thalassospira sp. TSL5-1; Pseudobutyrivibrio OR37; Bacteroides ifae; Polyphyromonasaceae KH3CP3RA; Listeria liparia; and Insolitisspirillum peregrinum.

In a particular aspect, the C2c2 protein according to the invention is, or is derived from, one of the orthologues shown in the table below. Alternatively, it is a chimeric protein of two or more of the orthologues shown in the table below. Alternatively, it is a mutant or variant (or chimeric mutant or variant) of one of the orthologues shown in the table below. The C2c2 proteins include dead C2c2, split C2c2, destabilized C2c2, fused or not with heterologous/functional domains, as described elsewhere herein.

In certain exemplary embodiments, the C2c2 effector protein is selected from Table 1 below (also including SEQ ID NOs:600-615).

The wild-type protein sequences for the above species are shown in Table 2 below. In certain aspects, nucleic acid sequences encoding C2c2 proteins are provided.

In one embodiment of the present invention, Leptotorichia shaii C2c2, Lachnospiraceae MA2020 C2c2, Lachnospiraceae NK4A179 C2c2, Clostridium aminophyllum (DSM 10710) C2c2, Carnobacterium gallinarum (DSM 4847) C2c2, Pardibacter pro Pionisigenes (WB4) C2c2, Listeria weihenstephanensis (FSL R9-0317) C2c2, Listeriaceae (FSL M6-0635) C2c2, Listeria newyokensis (FSL M6-0635) C2c2, Leptotorichia weedii Wild type sequence of any of (F0279) C2c2, Rhodobacter capsulata (SB 1003) C2c2, Rhodobacter capsulata (R121) C2c2, Rhodobacter capsulata (DE442) C2c2, Leptotricia weidii (Lw2) C2c2, or Listeria celigeri C2c2 An effector protein comprising an amino acid sequence having at least 80% sequence homology to is provided.

In one embodiment of the invention, the effector protein comprises an amino acid sequence with at least 80% sequence homology to the Type VI effector protein consensus sequence. Such consensus sequences include, but are not limited to, the consensus sequences described herein. According to the invention, a consensus sequence may be generated from multiple C2c2 orthologs. A consensus sequence can help determine the positions of conserved amino acid residues and motifs. Such consensus sequences include, but are not limited to, catalytic residues and HEPN motifs in C2c2 orthologues that mediate C2c2 function. One such consensus sequence is SEQ ID NO:325 generated from the above 33 orthologues using a Geneious Alignment.

In another non-limiting example, a sequence alignment tool to assist in generating consensus sequences and identifying conserved residues is the MUSCLE alignment tool (www.ebi.ac.uk/Tools/msa/muscle/). . For example, MUSCLE can be used to identify in Leptotrichia weedii C2c2 the following amino acid positions conserved among C2c2 orthologues: K2; K5; V6; E301; L331; D403; F446; I466; I470; R474 (HEPN); H475; H479 (HEPN), E508; Y863; L869; I872; K879; I933; L954; I958; R961; Y965; 11083; 11090.

An exemplary sequence alignment of HEPN domains showing highly conserved residues is shown in FIG.

In certain exemplary embodiments, the RNA target effector protein is a type VI-B effector protein, such as Casl3b and group 29 or 30 proteins. In certain exemplary embodiments, the RNA target effector protein comprises one or more HEPN domains. In certain exemplary embodiments, the RNA target effector protein comprises a C-terminal HEPN domain, an N-terminal HEPN domain, or both. For examples of type VI-B effector proteins that may be used in the context of the present invention, see below. U.S. patent application Ser. Smargon et al. “Cas13b is a Type VI-B CRISPR-associated RNA-Guided RNase differentially regulated by Accessory proteins Csx27 and Csx28 (Cas13b is a type VI-B CRISPR-associated RNA-guided RNase differentially regulated by accessory proteins Csx27 and Csx28)” Molecular Cell, 65, 1-13 (2017); dx.doi. org/10.1016/j.molcel.2016.12.023, and a provisional U.S. patent filed March 15, 2017, entitled "Novel Cas13b Orthologues CRISPR Enzymes and System." Patent application. In certain embodiments, the Casl3b enzyme is from Bergeyella zoohelcum. In certain other exemplary embodiments, the effector protein is an amino acid sequence having at least 80% sequence homology to any of the sequences shown in Table 3 (see also SEQ ID NOs:479-566), or including it.

In certain exemplary embodiments, the Class 2 Type VI CRISPR system is the Casl3c system. In certain exemplary embodiments, Casl3c orthologues are selected from Table 4 below. This table includes Cas13c orthologues expressed in mammalian cells.

ガイドＲＮＡ In certain exemplary embodiments, the RNA target effector protein is the Casl3c effector protein disclosed in 2017/047193. Examples of sequences of wild-type orthologs of Casl3c are shown in Table 5 below.

Guide RNA

As used herein, the terms "crRNA", "guide RNA", "single-stranded guide RNA", "gRNA" include any polynucleotide sequence with sufficient complementarity to a target nucleic acid sequence, and directs the sequence-specific binding of an RNA target complex comprising a gRNA and a CRISPR effector protein to a target nucleic acid sequence. In general, the gRNA is (i) capable of forming a complex with a CRISPR effector protein, and (ii) contains a sequence with sufficient complementarity to the target polynucleotide sequence to hybridize with the target sequence, thereby forming a CRISPR complex. It can be any polynucleotide sequence that directs sequence-specific binding to a target sequence. As used herein, the term "capable of forming a complex with a CRISPR effector protein" means that a complex capable of binding sequence-specifically to a target RNA can be formed and exert a function on that target RNA. It refers to the gRNA having a structure that allows the CRISPR effector protein to specifically bind to the gRNA. Structural components of gRNAs may include direct repeats and guide sequences (ie, spacers). Sequence-specific binding to target RNA is mediated by a "guide sequence" that is part of the gRNA. The guide sequence is complementary to the target RNA. In embodiments of the present invention, the term "guide RNA", ie an RNA capable of directing Cas to a target locus, is used similarly as in the above cited references such as WO2014/093622 (PCT/US2013/074667). As used herein, the term "guide sequence is capable of hybridizing" refers to a gRNA having sufficient complementarity to a target sequence to hybridize with the target sequence and mediate binding of the CRISPR complex to the target RNA. say a small part of In general, a guide sequence is any polynucleotide sequence that has sufficient complementarity with a target polynucleotide sequence to hybridize with the target sequence and direct sequence-specific binding of the CRISPR complex to the target sequence. In some embodiments, the degree of complementarity between the guide sequence and the corresponding target sequence is about 50%, 60%, 75%, 80%, 85%, 90% when optimally aligned using a suitable alignment algorithm. %, 95%, 97.5%, 99% or more. A suitable alignment may be determined using any suitable algorithm for aligning sequences. Non-limiting examples of such algorithms include the Smith-Waterman algorithm, the Needleman-Wunsch algorithm, algorithms based on the Burrows-Wheeler transform (e.g. the Burrows Wheeler Aligner), ClustalW, Clustal X, BLAT, Novoalign (from Novocraft Technologies). novocraft.com), ELAND (Illumina, San Diego, Calif.), SOAP (available at soap.genomics.org.cn), and Maq (available at maq.sourceforge.net).

In certain aspects, the CRISPR systems provided herein may utilize crRNA or analogue polynucleotides that include guide sequences. Here, the polynucleotide is RNA, DNA, or a mixture of RNA and DNA, and/or said polynucleotide comprises one or more nucleotide analogues. This array may contain any structure. Such structures include, but are not limited to, those of native crRNAs such as bulges (double strands with extra bases), hairpins, or stem-loop structures. In certain aspects, a polynucleotide comprising a guide sequence forms a duplex with a second polynucleotide sequence. The second polynucleotide sequence may be an RNA sequence or a DNA sequence.

In certain aspects, chemically modified guide RNAs are used. Examples of chemical modifications of the guide RNA include, but are not limited to, 2′-O-methyl (M) to one or more terminal nucleotides, 2′-O-methyl 3′-phosphorothioate (MS), or Incorporation of 2′-O-methyl=3′-thioPACE (MSP) is included. Such chemically modified guide RNAs may have increased stability and activity compared to unmodified guide RNAs, but target and non-target specificity is unpredictable. (See Hendel, 2015, Nat Biotechnol. 33(9):985-9, doi: 10.1038/nbt.3290 (published online June 29, 2015)). Chemically modified guide RNAs include, but are not limited to, RNAs with phosphorothioic acid linkages and bridging artificial nucleic acid (LNA) nucleotides containing methylene bridges between the 2'- and 4'-carbons of the ribose ring. further includes

In some variations, the guide sequence is about , 30, 35, 40, 45, 50, 75 nucleotides or longer. In some variations, the guide sequence has a length of less than about 75, 50, 45, 40, 35, 30, 25, 20, 15, 12 nucleotides. Preferably, the guide sequence is 10-30 nucleotides in length. The ability of the guide sequence to direct sequence-specific binding of the CRISPR complex to the target sequence may be assessed by any suitable assay. providing a host cell with the corresponding target sequence with sufficient components of the CRISPR system to form a CRISPR complex comprising the guide sequence to be tested, e.g., by transfecting with a vector encoding the component of the CRISPR sequence; Preferential cleavage within the target sequence may be assessed, such as with a Surveyor assay. Similarly, by providing a target sequence, a component of the CRISPR complex (including the guide sequence to be tested), and a control guide sequence that is different from the guide sequence to be tested, the reaction of the test guide sequence and the control guide sequence Cleavage of the target RNA may be assessed in vitro by comparing binding or cleavage rates at . Other assays are possible and obvious to those skilled in the art.

Guide sequences, and thus nucleic acid-targeted guide RNAs, may be selected to target any target nucleic acid sequence. In the context of CRISPR complex formation, "target sequence" refers to a sequence designed to be complementary to a guide sequence, wherein hybridization of the target sequence with the guide sequence facilitates formation of the CRISPR complex. . A target sequence may comprise an RNA polynucleotide. The term "target RNA" refers to an RNA polynucleotide that is or contains a target sequence. In other words, the target RNA is a portion of the gRNA, i.e., an RNA polynucleotide or RNA polynucleotide designed to be complementary to the guide sequence, to which the effector function mediated by a complex comprising the CRISPR effector protein and the gRNA is directed. may be part of In some embodiments, the target sequence is located in the nucleus or cytoplasm of the cell. The target sequence may be DNA. A target sequence may be any RNA sequence. In some embodiments, the target sequence is messenger RNA (mRNA), precursor mRNA, ribosomal RNA (rRNA), transfer RNA (tRNA), microRNA (miRNA), small interfering RNA (siRNA), small nuclear RNA (snRNA) ), small nucleolar RNA (snoRNA), double-stranded RNA (dsRNA), noncoding RNA (ncRNA), long noncoding RNA (lncRNA), and small cytoplasmic RNA (scRNA) It may be a sequence within an RNA molecule. In some preferred embodiments, the target sequence may be a sequence within an RNA molecule selected from the group consisting of mRNA, precursor mRNA, and rRNA. In some preferred embodiments, the target sequence may be a sequence within an RNA molecule selected from the group consisting of ncRNA and lncRNA. In some more preferred embodiments, the target sequence may be a sequence within an mRNA molecule or a precursor mRNA molecule.

In some aspects, the nucleic acid-targeted guide RNA is selected to reduce the degree of secondary structure within the RNA-targeted guide RNA. In some embodiments, about 75%, 50%, 40%, 30%, 25%, 20%, 15%, 10%, 5%, 1% or less of the nucleotides of the nucleic acid target guide RNA are self-folding when optimally folded. Participates in the formation of complementary base pairs. Optimal folding may be determined by any suitable polynucleotide folding algorithm. Some programs are based on calculating the minimum Gibbs free energy. An example of such an algorithm is mFold, described by Zuker and Stiegler (Nucleic Acids Res. 9 (1981), 133-148). Another exemplary folding algorithm is the line webserver RNAfold, which uses a centroid structure prediction algorithm developed at the Institute for Theoretical Chemistry, University of Vienna (e.g., A.R. Gruber et al., 2008, Cell 106(1): 23- 24; and PA Carr and GM Church, 2009, Nature Biotechnology 27(12): 1151-62).

In certain aspects, the guide RNA or crRNA may comprise, consist essentially of, or consist of a direct repeat (DR) sequence and a guide or spacer sequence. In certain aspects, the guide RNA or crRNA may comprise, consist essentially of, or consist of a direct repeat sequence fused or linked to a guide or spacer sequence. In certain embodiments, the direct repeat sequence may be located upstream (ie, 5') to the guide or spacer sequence. In other embodiments, the direct repeat sequence may be located downstream (ie, 3') of the guide or spacer sequence.

In certain aspects, the crRNA comprises a stem-loop, preferably a single stem-loop. In certain aspects, the direct repeats form a stem loop, preferably a single stem loop.

In certain aspects, the spacer length of the guide RNA is 15-35 nt. In particular aspects, the spacer length of the guide RNA is at least 15 nucleotides, preferably at least 18 nt, such as at least 19, 20, 21, 22 nt, or more. In certain aspects, the spacer length is 15-17 nt, such as 15, 16, or 17 nt, 17-20 nt, such as 17, 18, 19, or 20 nt, 20-24 nt, such as 20, 21, 22, 23, or 24 nt, 23-25 nt, such as 23, 24, or 25 nt, 24-27 nt, such as 24, 25, 26, or 27 nt, 27-30 nt, such as 27, 28, 29, or 30 nt, 30-35 nt, For example, 30, 31, 32, 33, 34, or 35 nt, or greater than or equal to 35 nt.

In certain aspects, the spacer length of the guide RNA is less than 28 nucleotides. In certain aspects, the spacer length of the guide RNA is at least 18 nucleotides and less than 28 nucleotides. In certain aspects, the spacer length of the guide RNA is 19-28 nucleotides. In certain aspects, the spacer length of the guide RNA is 19-25 nucleotides. In certain aspects, the spacer length of the guide RNA is 20 nucleotides. In certain aspects, the spacer length of the guide RNA is 23 nucleotides. In certain aspects, the spacer length of the guide RNA is 25 nucleotides.

In conventional CRISPR-Cas systems, the degree of complementarity between the guide sequence and its corresponding target sequence is approximately 50%, 60%, 75%, 80%, 85%, 90%, 95%, 97.5%. , 99% or more, or 100%. The guide, RNA, or sgRNA has a length of about It can be 28, 29, 30, 35, 40, 45, 50, 75 nucleotides or more. Alternatively, the guide, RNA or sgRNA may be about 75, 50, 45, 40, 35, 30, 25, 20, 15, 12 nucleotides or less in length. However, an aspect of the invention is to reduce non-target interactions, eg, reduce guides interacting with target sequences with low complementarity. Indeed, in these examples, the present invention provides non-target sequences with 80% to about 95% complementarity, such as 83%-84%, 88-89%, or 94-95% complementarity. Include mutations that result in a CRISPR-Cas system that can discriminate between target sequences (e.g., between 18-nucleotide targets and 18-nucleotide non-targets with 1, 2, or 3 mismatches). It is shown. Thus, in the context of the present invention, the degree of complementarity between a guide sequence and its corresponding target sequence is 94.5%, 95%, 95.5%, 96%, 96.5%, 97%, 97.5 %, 98%, 98.5%, 99%, 99.5%, greater than 99.9%, or 100%. Non-targets have 100%, 99.9%, 99.5%, 99%, 99%, 98.5%, 98%, 97.5%, 97%, 96.5% complementarity of sequence and guide , 96%, 95.5%, 95%, 94.5%, 94%, 93%, 92%, 91%, 90%, 89%, 88%, 87%, 86%, 85%, 84%, less than 83%, 82%, 81%, or 80%, preferably the non-target has 100%, 99.9%, 99.5%, 99%, 99%, 98% complementarity between the sequence and the guide. .5%, 98%, 97.5%, 97%, 96.5%, 96%, 95.5%, 95%, 94.5%.

In certain aspects, the introduction of mismatches, e.g., one or more mismatches (e.g., 1 or 2 mismatches) between the spacer sequence and the target sequence, reduces the cleavage efficiency, including the mismatched positions along the spacer/target. can be adjusted. For example, cleavage efficiency is more affected if the double mismatch is more central (ie, not 3' or 5'). Thus, by choosing mismatched positions along the spacer, cleavage efficiency can be modulated. For example, if less than 100% cleavage of the target (eg, in a cell population) is desired, one or more, eg, preferably two mismatches between the spacer and the target sequence may be introduced into the spacer sequence. If it is more central along the mismatched spacer, the cleavage rate will be lower.

In certain exemplary embodiments, cleavage efficiency is used to distinguish between two or more targets that differ by a single nucleotide, e.g., single nucleotide polymorphisms (SNPs), diversity, or (point) mutations. A single-stranded guide may be designed that allows A CRISPR effector may have reduced sensitivity to SNPs (or other single nucleotide diversity) and subsequently cleave SNP targets with a certain level of efficiency. Thus, for two targets or a set of targets, a guide RNA may be designed with a nucleotide sequence complementary to one of the targets, ie the target SNP. Guide RNAs are further designed to have synthetic mismatches. As used herein, the term "synthetic mismatch" refers to a naturally occurring SNP upstream or downstream, up to 5 nucleotides upstream or downstream, 4, 3, 2, or 1 nucleotides upstream or downstream, preferably up to 3 nucleotides upstream. or downstream, more preferably up to 2 nucleotides upstream or downstream, most preferably 1 nucleotide upstream or downstream (ie adjacent to the SNP) introduced non-naturally occurring discrepancies. When the CRISPR effector binds to the target SNP, only one mismatch with the synthetic mismatch is formed and the CRISPR effector remains activated producing a detectable signal. When the guide RNA hybridizes to a non-target SNP, two mismatches are formed, the SNP-derived mismatch and the synthetic mismatch, and no detectable signal is generated. Accordingly, the systems disclosed herein may be designed to distinguish SNPs within a population. For example, the system may be used to distinguish between different pathogen strains with a single SNP, or to detect SNPs specific to a particular disease. Such SNPs include, but are not limited to, disease-associated SNPs, but are not limited to cancer-associated SNPs.

In particular aspects, the guide RNA has SNPs (starting at the 5' end) of the spacer sequence at positions 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, Designed to be located at 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30. In certain aspects, the guide RNA is designed so that the SNP is located at positions 1, 2, 3, 4, 5, 6, 7, 8, or 9 of the spacer sequence (starting at the 5' end). In certain aspects, the guide RNA is designed such that the SNP is located at positions 2, 3, 4, 5, 6, or 7 of the spacer sequence (starting at the 5' end). In certain aspects, the guide RNA is designed so that the SNP is located at positions 3, 4, 5, or 6 of the spacer sequence (starting from the 5' end). In certain aspects, the guide RNA is designed such that the SNP is located at position 3 of the spacer sequence (starting at the 5' end).

In certain aspects, the guide RNA is such that the mismatch (e.g., a synthetic mismatch, or another variation of the SNP) is (starting at the 5' end) the spacer sequence at positions 1, 2, 3, 4, 5, 6, Located at 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 is designed to In certain aspects, the guide RNA is designed so that the mismatch is located at positions 1, 2, 3, 4, 5, 6, 7, 8, or 9 of the spacer sequence (starting at the 5' end). In certain aspects, the guide RNA is designed so that the mismatch is located at positions 4, 5, 6, or 7 of the spacer sequence (starting at the 5' end). In certain aspects, the guide RNA is designed such that the mismatch is located at position 5 of the spacer sequence (starting at the 5' end).

In certain aspects, the guide RNA is designed so that the mismatch is located two nucleotides upstream of the SNP (ie, one nucleotide in between).

In certain aspects, the guide RNA is designed such that the mismatch is located two nucleotides downstream of the SNP (ie, one nucleotide in between).

In certain aspects, the guide RNA is designed such that the mismatch is located at position 5 of the spacer sequence (starting from the 5' end) and the SNP is located at position 3 of the spacer sequence (starting from the 5' end). .

Embodiments described herein are eukaryotic cells (ex vivo, i.e., isolated eukaryotic cells), comprising delivering the vectors described herein to cells as described herein. ) to induce one or more nucleotide modifications. Mutations may involve the introduction, deletion or substitution of one or more nucleotides in each target sequence of the cell via one or more guide RNAs. Mutations may involve the introduction, deletion or substitution of 1-75 nucleotides in each target sequence of said cell via one or more guide RNAs. The mutation is 1, 5, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 at each target sequence of said cell via one or more guide RNAs. , 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, or 75 nucleotides introduced, deleted, or substituted. The mutation is at each target sequence of said cell via one or more guide RNAs , 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, or 75 nucleotides introduced, deleted, or substituted. Mutations are mediated by one or more guide RNAs at each target sequence in said cell. , 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, or 75 nucleotides introduced, deleted, or substituted. Mutations are mediated by one or more guide RNAs at each target sequence in said cell. , or an introduction, deletion, or substitution of 75 nucleotides. Mutations include the introduction, deletion, or substitution of 40, 45, 50, 75, 100, 200, 300, 400, or 500 nucleotides at each target sequence in said cell via one or more guide RNAs. You can stay.

Typically, in the context of an endogenous CRISPR system, once a CRISPR complex (comprising a guide sequence hybridized to a target sequence and complexed with one or more Cas proteins) is formed, the target sequence , or near (e.g., within 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 50, or more base pairs from the target sequence), but Especially for RNA targets, for example, it may depend on secondary structure.

RNA-based masking constructs

As used herein, the term "masking construct" refers to a molecule that can be cleaved or inactivated by an activated CRISPR system effector protein as described herein. The term "masking construct" may also be alternatively referred to as "detection construct". In certain exemplary embodiments, the masking construct is an RNA-based masking construct. A masking construct prevents the production or detection of a detectable positive signal. A detectable positive signal can be any signal that can be detected using optical, fluorescent, chemiluminescent, electrochemical, or other detection methods known in the art. The masking construct may prevent production of a detectable positive signal or mask the presence of a detectable positive signal until the masking construct is removed or otherwise silenced. The term "detectable positive signal" is used to distinguish from other detectable signals detectable in the presence of the masking construct. For example, in certain embodiments, the first signal may be detected in the presence of a masking agent (ie, a detectable negative signal). The first signal is then converted to a second signal (eg, a detectable positive signal) upon detection of the target molecule by an activated CRISPR effector protein and cleavage or inactivation of the masking factor.

In certain exemplary embodiments, a masking construct may suppress production of a gene product. A gene product may be encoded by a reporter construct added to the sample. A masking construct may be an interfering RNA that participates in the RNA interference pathway, eg, shRHN or siRNA. Masking constructs may also include microRNAs (miRNAs). The presence of the masking construct suppresses expression of the gene product. The gene product may be a fluorescent protein or other RNA transcript or protein detectable by labeled probes or antibodies for the presence of the masking construct. Upon activation of the effector protein, the masking construct is cleaved or silenced allowing the gene product to be expressed and detected as a detectable positive signal.

In certain exemplary embodiments, the masking construct provides one or more reagents necessary to produce a positive signal, and release of the one or more reagents from the masking construct produces a detectable positive signal. It may be isolated as One or more reagents may be conjugated to produce a colorimetric, chemiluminescent, fluorescent, or any other detectable signal, and any reagent found suitable for such purposes. of reagents. In certain exemplary embodiments, one or more reagents are sequestered by an RNA aptamer that binds the one or more reagents. Upon detection of the target molecule, one or more reagents are released upon activation of the effector protein. In certain exemplary embodiments, one or more reagents are proteins (eg, enzymes) that can readily produce detectable signals, such as colorimetric, chemiluminescent, or fluorescent signals. Such reagents are designed to bind one or more RNA aptamers to a protein, thereby inhibiting or sequestering that protein from producing a detectable signal. Upon activation of the effector proteins disclosed herein, the RNA aptamer is cleaved or degraded so that it cannot interfere with the protein's ability to generate a detectable signal. In certain exemplary embodiments, the aptamer is a thrombin-inhibiting aptamer. In certain exemplary embodiments, the thrombin-inhibiting aptamer has the sequence GGGAACAAAGCUGAAGUACUUACCC (SEQ ID NO:414). Cleavage of this aptamer activates thrombin to cleave a peptide colorimetric or fluorogenic substrate. In certain exemplary embodiments, the colorimetric substrate is paranitroanilide covalently linked to a peptide substrate of thrombin (pNA). When cleaved by thrombin, pNA is released, turning yellow and easily visible. In certain exemplary embodiments, the fluorescent substrate is 7-amino-4-methylcoumarin, a blue fluorophore that can be detected using a fluorescence detector. Within the above principles, inhibitory aptamers against horseradish peroxidase (HRP), β-galactosidase, or calf alkaline phosphatase (CAP) may be used.

In certain aspects, RNase activity is detected colorimetrically by cleavage of an enzyme-inhibiting aptamer. One possible mode of converting RNase activity into a colorimetric signal is to couple RNA aptamer cleavage with reactivation of the enzyme that can produce a colorimetric output. Absent RNA cleavage, the intact aptamer binds to the enzymatic target and inhibits its activity. The advantage of this readout system is that the enzyme provides an additional amplification step. Once released from the aptamer by a secondary activity (eg, a Casl3a secondary activity), the colorimetric enzyme continues to produce colorimetric product and increase signal.

In certain aspects, existing aptamers that inhibit the enzyme with a colorimetric readout are used. There are several aptamer/enzyme pairs with colorimetric readouts, such as thrombin, protein C, neutrophil elastase, and subtilisin. These proteases have pNA-based colorimetric substrates and are commercially available. In certain embodiments, novel aptamers that target common colorimetric enzymes are used. Aptamers designed by selection methods such as SELEX can be engineered to target robust general enzymes (eg, β-galactosidase, horseradish peroxidase, or calf intestinal alkaline phosphatase). Such methods allow rapid selection of aptamers with nanomolar binding efficiencies. Such methods can also be used to develop additional enzyme/aptamer pairs for colorimetric readout.

In certain aspects, RNase activity is detected colorimetrically by cleavage of the RNA binding inhibitor. Many common colorimetric enzymes have competitive and reversible inhibitors. For example, β-galactosidase can be inhibited by galactose. Although many of these inhibitors are weak, their effects can increase with increasing local concentration. By coupling the local concentration of inhibitor with the RNase activity, a pair of colorimetric enzyme and inhibitor can be engineered into the RNase sensor. A small-molecule inhibitor-based colorimetric RNase sensor consists of three components: a colorimetric enzyme, an inhibitor, and a bridging RNA that covalently binds both the inhibitor and the enzyme to bind the inhibitor to the enzyme. including. In the uncleaved configuration, the increased local concentration of the small molecule inhibits the enzyme. When the RNA is cleaved (eg, by Casl3a secondary cleavage), the inhibitor is released and the colorimetric enzyme is activated.

In certain aspects, RNase activity is detected colorimetrically by guanine quadruplex formation and/or activation. Guanine quadruplexes of DNA may bind heme (iron(III)-protoporphyrin IX) to form a DNA enzyme with peroxidase activity. When supplied with a peroxidase substrate (eg, ABTS: (2,2′-azinobis[3-ethylbenzothiazoline-6-sulfonic acid] diammonium salt)), the guanine quadruplex-heme complex undergoes peroxidation. Oxidizes the substrate in the presence of hydrogen. This causes the color of the solution to turn green. An exemplary guanine quadruplex forming DNA sequence is GGGTAGGGCGGGTTGGGA (SEQ ID NO: 415). Hybridizing an RNA sequence to this DNA aptamer limits the formation of guanine quadruplex structures. Upon RNase subactivation (eg, C2c2-complex subactivation), the anchorage of RNA is cleaved to form guanine quadruplexes and heme can bind. This method is particularly attractive because color formation is enzymatic, implying that there is additional amplification beyond RNase activation.

In certain exemplary embodiments, masking constructs may be immobilized to solid substrates within discrete volumes (defined further below) to isolate one reagent. For example, a reagent may be a bead containing a dye. When isolated by the immobilized reagent, the individual beads are so dispersed that they cannot produce a detectable signal, but when released from the masking construct they produce a detectable signal, for example by agglutination or simply by increasing the concentration of the solution. can be generated. In certain exemplary embodiments, the immobilized masking factor is an RNA-based aptamer that can be cleaved by activated effector proteins upon detection of the target molecule.

In certain other exemplary embodiments, the masking construct binds to immobilized reagents in solution, thereby enhancing the ability of the reagents to bind to discrete labeled binding partners that are free in solution. impede. Thus, when the sample is subjected to a washing step, the labeled binding partner may be washed out of the sample in the absence of the target molecule. However, upon activation of the effector protein, the masking construct is cleaved sufficiently to inhibit the ability of the masking construct to bind the reagent, thereby binding the labeled binding partner to the immobilized reagent. be able to. Therefore, the labeled binding partner remained after the washing step, indicating the presence of the target molecule in the sample. In certain aspects, the masking construct that binds to the immobilized reagent is an RNA aptamer. The immobilized reagent may be a protein and the labeled binding partner may be a labeled antibody. Alternatively, the immobilized reagent can be streptavidin and the labeled binding partner can be labeled biotin. The binding partner label used in the above embodiments may be any detectable label known in the art. Other known binding partners may also be used with the overall design described above.

In certain exemplary embodiments, a masking construct may comprise a ribozyme. Ribozymes Ribozymes are RNA molecules with catalytic properties. Ribozymes, whether naturally occurring or artificial, comprise or consist of RNA that may be targeted by the effector proteins disclosed herein. A ribozyme may be selected or engineered to catalyze a reaction that either produces a detectable negative signal or inhibits production of a positive control signal. Upon inactivation of the ribozyme by activated effector protein molecules, the reaction either produces a negative control signal or removes inhibitors to the production of a detectable positive signal, thereby detecting a detectable positive signal. enable In one exemplary embodiment, the ribozyme may catalyze a colorimetric reaction causing the solution to assume a first color. When the ribozyme is deactivated, the solution assumes a second color and the second color is a detectable positive signal. An example of how a ribozyme can be used to catalyze a colorimetric reaction is given by Zhao et al. "Signal amplification of glucosamine-6-phosphate based on ribozyme glmS," ” Biosens Bioelectron. 2014; 16:337-42. Also provided are examples of modifying such systems to work in the context of the embodiments disclosed herein. Alternatively, ribozymes may produce cleavage products, such as RNA transcripts, if present. Accordingly, detection of a detectable positive signal may include detection of uncleaved RNA transcripts produced only in the absence of the ribozyme.

In one exemplary embodiment, the masking construct comprises a detection agent that changes color depending on whether it is aggregated or dispersed in solution. For example, certain nanoparticles (eg, colloidal gold) visually change their color from purple to red as aggregates become dispersed particles. Thus, in certain exemplary embodiments, such detection agents may be carried to aggregates by one or more bridging molecules. For example, see FIG. At least some of the bridging molecules comprise RNA. Upon activation of the effector proteins disclosed herein, the RNA portion of the bridging molecule is cleaved, dispersing the detection agent and resulting in a corresponding color change. For example, see FIG. In certain exemplary embodiments, the bridging molecule is an RNA molecule. In certain exemplary embodiments, the detection agent is a colloidal metal. Colloidal metal materials may comprise water-insoluble metal particles or metal compounds dispersed in a liquid, hydrosol, or metal sol. Colloidal metals may be selected from Group IA, IB, IIB, and IIIB metals, transition metals, especially Group VIII metals of the periodic table. Preferred metals include gold, silver, aluminum, ruthenium, zinc, iron, nickel, and calcium. Other suitable metals also include all of the various oxidation states of the following metals: lithium, sodium, magnesium, potassium, scandium, titanium, vanadium, chromium, manganese, cobalt, copper, gallium, strontium, niobium, molybdenum, palladium, indium, tin, tungsten, rhenium, platinum, and gadolinium. These metals are preferably provided in ionic form (eg, Al ³⁺ , Ru ³⁺ , Zn ²⁺ , Fe ³⁺ , Ni ²⁺ , and Ca ²⁺ ions) generated from suitable metal compounds.

The above color change is observed when the RNA bridge is cleaved by an activated CRISPR effector. In certain exemplary embodiments, these particles are colloidal metals. In certain other exemplary embodiments, the colloidal metal is colloidal gold. In certain exemplary embodiments, the colloidal nanoparticles are 15 nm gold nanoparticles (AuNPs). Due to the inherent surface properties of colloidal gold nanoparticles, maximum absorbance is observed at 520 nm when fully dispersed in solution and visually red. As the AuNPs aggregate, the absorbance maximum changes to red, darkens in color, and finally precipitates out of solution as dark purple aggregates. In certain exemplary embodiments, nanoparticles are modified to include DNA linkers extending from the surface of the nanoparticles. Individual particles are bound together by single-stranded RNA (ssRNA) bridges that hybridize each end of the RNA to at least a portion of the DNA linker. The nanoparticles are thus forming a web of bound particles and agglomerates and appear as a dark precipitate. Upon activation of the CRISPR effectors disclosed herein, the ssRNA cross-links are cleaved, releasing the AuNPs from the binding mesh and making them visually red. Examples of DNA linkers and RNA bridging sequences are shown below. A thiol linker at the end of the DNA linker may be used as a surface to bind AuNPs. Other forms of attachment may be used. In certain exemplary embodiments, two AuNP populations may be generated, one for each DNA linker. This helps facilitate proper binding of the ssRNA bridges in proper orientation. In certain exemplary embodiments, the first DNA linker is attached to the 3' end and the second DNA linker is attached to the 5' end.

In some embodiments, one or more elements of the nucleic acid targeting system are derived from a particular organism, including endogenous CRISPR RNA targeting systems. In particular embodiments, the CRISPR RNA targeting system is found in Eubacterium and Ruminococcus. In certain aspects, the effector protein comprises a targeted RNA cleaving activity and a secondary ssRNA cleaving activity. In certain aspects, the effector protein comprises two HEPN domains. In certain aspects, the effector protein lacks a partner in the Helical-1 domain of Casl3a. In a particular aspect, the effector protein is smaller than the Class 2 CRISPR effector described above (median size of 928 amino acids (aa)). The median value of this magnitude was 190 aa (17%) less than the median value of Cas13c, greater than 200 aa (18%) less than the median value of Cas13b, and greater than 300 aa (26%) less than the median value of Cas13a smaller than the central value of In certain aspects, the effector protein has no requirement for flanking sequences (eg, PFS, PAM).

In certain aspects, the effector protein locus structure comprises a WYL domain containing accessory proteins (the accessory proteins are indicated after the three conserved amino acids in the groups from which these domains were identified; e.g., See WYL domain IPR026881). In certain aspects, the WYL domain accessory protein comprises at least one helix-turn-helix (HTH) or ribbon-helix-helix (RHH) DNA binding domain. In certain aspects, the WYL domain containing accessory protein enhances both the targeted RNA cleaving activity and the secondary ssRNA cleaving activity of the RNA target effector protein. In certain aspects, the WYL domain containing the accessory protein comprises an N-terminal RHH domain and a primary conserved pattern of hydrophobic residues, including an invariant tyrosine-leucine doublet corresponding to the original WYL motif. . In a particular aspect, the WYL domain containing accessory protein is WYL1. WYL1 is a single WYL domain protein that is primarily associated with Ruminococcus.

In another exemplary embodiment, the Type VI RNA-targeted Cas enzyme is Casl3d. In certain embodiments, Cas13d is Eubacterium silaeum DSM 15702 (EsCas13d) or Ruminococcus N15.MGS-57 sp. (RspCas13d) (e.g., Yan et al., Cas13d Is a Compact RNA-Targeting Type VI CRISPR Effector Positively Modulated by a WYL-Domain-Containing Accessory Protein, Molecular Cell (2018), doi.org/10.1016/j.molcel.2018.02.028). RspCasl3d and EsCasl3d have no requirements for flanking sequences (eg PFS, PAM).

In certain other exemplary embodiments, a masking construct may comprise an RNA oligonucleotide to which a detectable label and a detectable-label masking agent are attached. An example of such a detectable label/masking agent pair is a fluorophore and a quencher for that fluorophore. Quenching of the fluorophore can occur as a result of the formation of non-fluorescent complexes between the fluorophore and other fluorophores or non-fluorescent molecules. This reaction mechanism is known as ground-state complexation, static quenching, or catalytic quenching. Thus, RNA oligonucleotides may be designed such that the fluorophore and the quencher are in sufficient proximity for contact quenching to occur. Fluorophores and their associated quenchers are known in the art and may be selected by one of ordinary skill in the art for this purpose. The particular fluorophore/quencher pair is not critical in the context of the present invention, except that the choice of fluorophore/quencher pair ensures that the fluorophore is masked. Upon activation of the effector proteins disclosed herein, the RNA oligonucleotide is cleaved, breaking the proximity of the fluorophore and quencher required to maintain the contact quenching effect. Thus, detection of fluorophores may be used to determine the presence of target molecules in a sample.

In certain other exemplary embodiments, a masking construct may comprise one or more RNA oligonucleotides appended with one or more metal nanoparticles (eg, gold nanoparticles). In some variations, the masking construct comprises a plurality of metal nanoparticles crosslinked by a plurality of RNA oligonucleotides forming closed loops. In one aspect, the masking construct comprises 3 gold nanoparticles bridged by 3 RNA oligonucleotides forming a closed loop. In some embodiments, the metal nanoparticles produce a detectable signal upon cleavage of the RNA oligonucleotide by the CRISPR effector protein.

In certain other exemplary embodiments, a masking construct may comprise one or more RNA oligonucleotides to which one or more quantum dots are attached. In some embodiments, the quantum dots produce a detectable signal upon cleavage of the RNA oligonucleotide by the CRISPR effector protein.

In one exemplary embodiment, the masking constructs may include quantum dots. A quantum dot may have a plurality of linker molecules attached to its surface. At least a portion of the linker molecule comprises RNA. A linker molecule is attached at one end to the quantum dot and one at either end along the length of the linker or at its end to keep the quenchers in close enough proximity for quantum dot quenching to occur. quencher is added. A linker may be branched. As noted above, the quantum dot/quencher pair is not critical other than ensuring that the fluorophore is masked by the quantum dot/quencher pair. Quantum dots and their associated quenchers are known in the art and may be selected by one of ordinary skill in the art for this purpose. Upon activation of the effector proteins disclosed herein, the RNA portion of the linker molecule is cleaved, thereby maintaining the necessary proximity of the quantum dot to one or more quenchers to maintain the quenching effect. Eliminate. In certain exemplary embodiments, the quantum dots are conjugated with streptavidin. The RNA was attached via a biotin linker to give the sequence /5Biosg/UCUCGUACGUUC/3IAbRQSp/ (SEQ ID NO: 416) or /5Biosg/UCUCGUACGUUCUCUCGUACGUUC/3IAbRQSp/ (SEQ ID NO: 417) (where /5Biosg/ is the biotin tag and / 31AbRQSp/ is an Iowa Black quencher) to recruit the quencher molecule. When cleaved by the activating effectors disclosed herein, the quantum dots emit visible fluorescence.

Similarly, Forster resonance energy transfer (FRET) may be used to generate a detectable positive signal. FRET occurs when a photon from an energy-excited fluorophore (i.e., the "donor fluorophore") shifts the electronic energy state of another molecule (i.e., the "acceptor") to an excited singlet state at a higher vibrational level. It is a non-radiative process that raises The donor fluorophore returns to the ground state without emitting fluorescence characteristic of that fluorophore. Receptors may be other fluorophores or non-fluorescent molecules. If the acceptor is a fluorophore, the transferred energy is emitted as fluorescence characteristic of that fluorophore. If the acceptor is a non-fluorescent molecule, the absorbed energy is lost as heat. Thus, in the context of the embodiments disclosed herein, a fluorophore/quencher pair is replaced with a donor fluorophore/acceptor pair attached to an oligonucleotide molecule. When intact, the masking construct produces a first signal (detectable negative signal) that is detected as fluorescence or heat emitted from the receptor. Upon activation of the effector proteins disclosed herein, the RNA oligonucleotide is cleaved such that FRET is inhibited and the fluorescence of the donor fluorophore is detected (as a detectable positive signal). Become.

In certain exemplary embodiments, masking constructs involve the use of intercalating dyes whose absorbance changes in response to the cleavage of long RNAs into short nucleotides. Several such dyes exist. For example, pyronine-Y binds to RNA to form a complex with an absorbance of 572 nm. When this RNA is cleaved, it loses absorbance and changes color. Methylene blue may be used as well. Methylene blue changes absorbance at 688 nm when RNA is cleaved. Thus, in certain exemplary embodiments, a masking construct comprises RNA and an intercalating dye conjugate that changes absorbance upon cleavage of the RNA by an effector protein disclosed herein.

amplification

In certain exemplary embodiments, target RNA and/or DNA may be amplified prior to activating the CRISPR effector protein. Any suitable RNA or DNA amplification technique may be used. In certain exemplary embodiments, the RNA or DNA amplification is isothermal. In certain exemplary embodiments, the isothermal amplification is nucleic acid sequence amplification (NASBA), recombinase polymerase amplification (RPA), loop-mediated isothermal amplification (LAMP), strand displacement amplification (SDA), helicase dependent amplification (HDA), Or it may be a nicking enzyme amplification reaction (NEAR). In certain exemplary embodiments, non-isothermal amplification methods may be used, including but not limited to PCR, multiple displacement amplification (MDA), rolling circle amplification (RCA), ligase chain reaction (LCR), or branching. amplification method (RAM).

In certain exemplary embodiments, the RNA or DNA amplification is Nucleic Acid Sequence Amplification (NASBA), which initiates reverse transcription of target RNA by a sequence-specific reverse primer to create RNA/DNA duplexes. do. RNase H is then used to degrade the RNA template and bind a forward primer containing a promoter (eg, the T7 promoter) to initiate elongation of the complementary strand and generate a double-stranded DNA product. Copies of the target RNA sequence are then made by RNA polymerase promoter-mediated transcription of the DNA template. Importantly, the guide RNA allows detection of each new target RNA, which further increases the sensitivity of the assay. Binding of the target RNA by the guide RNA activates the CRISPR effector protein to proceed with the process outlined above. The NASBA reaction has the advantage of being able to proceed in more mild isothermal conditions (e.g., about 41° C.), making the system deployed for early direct detection in the field and away from clinical laboratories. and devices.

In certain other exemplary embodiments, a recombinase polymerase amplification (RPA) reaction may be used to amplify the target nucleic acid. The RPA reaction uses a recombinase that can pair sequence-specific primers with homologous sequences on double-stranded DNA. The presence of target DNA initiates DNA amplification and no other sample manipulation such as thermal cycling or chemical lysis is required. The entire RPA amplification system is stable as a dry formulation and can be safely shipped without refrigeration. The RPA reaction may also be carried out under isothermal conditions with an optimum reaction temperature of 37-42°C. Sequence-specific primers are designed to amplify sequences containing the target nucleic acid sequence to be detected. In certain exemplary embodiments, an RNA polymerase promoter (eg, T7 promoter) is added to one of the primers. This results in an amplified double-stranded DNA product containing the target sequence and the RNA polymerase promoter. Addition of RNA polymerase after or during the RPA reaction produces RNA from the double-stranded DNA template. Amplified target RNA may then be detected by a CRISPR effector system. Thus, the embodiments disclosed herein may be used to detect target DNA. An RPA reaction may be used to amplify the target RNA. The target RNA is first converted to cDNA using reverse transcriptase, followed by second strand DNA synthesis. At this time, the RPA reaction outlined above proceeds.

Thus, in certain exemplary embodiments, the systems disclosed herein may include amplification reagents. Different components or reagents useful for nucleic acid amplification are described herein. For example, the amplification reagents described herein may include a buffer such as Tris buffer. Tris buffer may be used at any concentration suitable for the desired application or use. Such concentrations include, but are not limited to, 1 mM, 2 mM, 3 mM, 4 mM, 5 mM, 6 mM, 7 mM, 8 mM, 9 mM, 10 mM, 11 mM, 12 mM, 13 mM, 14 mM, 15 mM, 25 mM, 50 mM, 75 mM, 1 M etc. One skilled in the art can determine the appropriate concentration of buffers, such as Tris, for use with the present invention.

Salts such as magnesium chloride (MgCl ₂ ), potassium chloride (KCl), or sodium chloride (NaCl) may be included in amplification reactions such as PCR to improve amplification of nucleic acid fragments. Salt concentrations will vary with the particular reaction and application, but in some embodiments, particular sized nucleic acid fragments may provide optimal results at particular salt concentrations. Larger products may require a change in salt concentration, typically a lower salt concentration, to achieve the desired result. On the other hand, for amplification of small products, higher salt concentrations give better results. As will be appreciated by those skilled in the art, the presence and/or concentration of salt may alter the stringency of a biological or chemical reaction along with changes in salt concentration, thus the present invention and herein Any salt that provides suitable conditions for the described reactions may be used.

Other components of a biological or chemical reaction may include a cell lysing component to break open or lyse cells for analysis of intracellular material. Cell lysing components include, but are not limited to, detergents, salts _of the above (eg, NaCl, KCl, ammonium sulfate [( _NH4 ) _2SO4 ], or others). Detergents that may be suitable for the present invention are Triton X-100, sodium dodecyl sulfate (SDS), CHAPS (3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate), ethyltrimethyl bromide Ammonium, nonylphenoxypolyethoxylethanol (NP-40) may be included. Detergent concentrations may vary depending on the particular application and may be reaction specific in some cases. Amplification reactions may contain dNTPs and nucleic acid primers used at any concentration suitable for the present invention. Such concentrations include, but are not limited to, 100 nM, 150 nM, 200 nM, 250 nM, 300 nM, 350 nM, 400 nM, 450 nM, 500 nM, 550 nM, 600 nM, 650 nM, 700 nM, 750 nM, 800 nM, 850 nM, 900 nM, 950 nM, 1 mM ,2 mM,3 mM,4 mM,5 mM,6 mM,7 mM,8 mM,9 mM,10 mM,20 mM,30 mM,40 mM,50 mM,60 mM,70 mM,80 mM,90 mM,100 mM,150 mM,200 mM,250 mM,300 mM,350 mM,400 mM,450 mM , 500 mM, and the like. Similarly, polymerases useful according to the invention may be any specific or universal polymerase known in the art and useful for the invention. Such polymerases include Taq polymerase, Q5 polymerase, and the like.

In some embodiments, the amplification reagents described herein may be suitable for use in hot-start amplification. Hot-start amplification, in some embodiments, allows adapter molecules to reduce or eliminate oligo dimerization, or otherwise prevent unwanted amplification products or artifacts, or obtain optimal amplification of desired products. may be useful for Many of the components described herein used for amplification may also be used for hot start amplification. In some embodiments, reagents or components suitable for use in hot start amplification may be substituted for one or more of the suitable compositional components. For example, polymerases or other reagents that exhibit the desired activity at specific temperatures or other reaction conditions may be used. In some embodiments, reagents designed or optimized for use in hot start amplification may be used. For example, a polymerase may be activated after transposition or after reaching a certain temperature. Such polymerases may be antibody-based or aptamer-based. The polymerases described herein are known in the art. Examples of such reagents may include, but are not limited to, hot-start polymerases, hot-start deoxynucleoside triphosphates (dNTPs), and photocaged dNTPs. Such reagents are known in the art and available. A person skilled in the art can determine the optimum temperature suitable for individual reagents.

Nucleic acids may be amplified using a particular thermocycling mechanism or apparatus and may be performed in a single reaction or in bulk such that any desired number of reactions are performed simultaneously. In some embodiments, amplification may be performed using a microfluidic or robotic device, or manually by varying the temperature to achieve the desired amplification. In some embodiments, optimization may be performed to obtain optimal reaction conditions for a particular application or material. Reaction conditions can be optimized to obtain sufficient amplification, as will be apparent to those skilled in the art.

In certain aspects, detection of DNA by methods or systems of the invention requires transcription of the (amplified) DNA into RNA prior to detection.

Enrichment of target RNA/DNA

In certain exemplary embodiments, the target RNA or DNA may first be enriched prior to detection or amplification of the target RNA or DNA. In certain exemplary embodiments, this enrichment may be achieved by binding of target nucleic acids by CRISPR effector systems.

Current target-specific enrichment test protocols require single-stranded nucleic acids prior to hybridization with probes. Among other advantages, this embodiment can eliminate this step and directly target double-stranded DNA (part or all of the double strand). Also, embodiments disclosed herein are enzyme-driven targeted methods that provide faster kinetics and simpler workflows to enable isothermal enrichment. In certain exemplary embodiments, concentration may occur at 20-37°C. Certain exemplary embodiments use a set of guide RNAs against different target nucleic acids in a single assay to detect multiple targets and/or multiple variants within a single target. It can be carried out.

In certain exemplary embodiments, death CRISPR effector proteins may be allowed to bind to target nucleic acids in solution and then isolated from the solution. For example, an antibody or other molecule (eg, an aptamer) that specifically binds to the death CRISPR effector protein may be used to isolate the death CRISPR effector protein bound to the target nucleic acid from solution.

In other exemplary embodiments, the death CRISPR effector protein may be bound to a solid substrate. An immobilized substrate may refer to any material suitable for attachment of polypeptides or polynucleotides or modified to do so. Possible substrates include, but are not limited to, glass and modified functional glass, plastics (acrylic, polystyrene and copolymers of styrene and other materials, polypropylene, polyethylene, polybutylene, polyurethane, Teflon etc.), polysaccharides, nylons, nitrocellulose, ceramics, resins, silica, silica-based materials including silicon and modified silicon, carbon, metals, inorganic glasses, plastics, optical fiber bundles, and various other polymers. be done. In some embodiments, the solid support comprises a patterned surface suitable for immobilizing molecules in an ordered pattern. In certain embodiments, a patterned surface refers to an array of distinct regions within or on an exposed layer of a solid support. In some embodiments, the solid support includes an array of surface wells or depressions. The composition and shape of the solid support may vary depending on its use. In some embodiments, the solid support is a planar structure such as a slide, chip microchip, and/or array. The surface of the substrate may thus be in the form of a planar layer. In some embodiments, the solid support comprises one or more surfaces of the flow cell. As used herein, the term "flow cell" refers to a chamber containing a solid surface through which one or more fluid reagents can flow. Examples of flow cells and associated fluidic systems and detection devices that can readily be used in the disclosed methods are described, for example, in Bentley et al. Nature 456:53-59 (2008), WO04/0918497. WO 91/06678; WO 07/123744; US 7,329,492; US 7,211,414; US 7,315,019; US 7,405 , 281, and US 2008/0108082. In some embodiments, the solid support or surface thereof is non-planar, such as the inner or outer surface of a tube or container. In some embodiments, the solid support comprises microspheres or beads. The terms "microspheres", "beads" and "particles" refer to small discrete particles of various materials in terms of solid substrates. Various materials include, but are not limited to, plastics, ceramics, glass, and polystyrene. In certain embodiments, the microspheres are magnetic microspheres or beads. Alternatively or additionally, the beads may be porous. Bead diameters range from nanometers (eg, 100 nm) to millimeters (eg, 1 mm).

A sample containing or suspected of containing the target nucleic acid may then be exposed to a substrate to allow the target nucleic acid to bind to the bound death CRISPR effector protein. Non-target molecules may then be washed away. In certain exemplary embodiments, the target nucleic acid may then be released from the CRISPR effector protein/guide RNA complex for further detection using the methods disclosed herein. In certain exemplary embodiments, the target nucleic acid may first be amplified as described herein.

In certain exemplary embodiments, CRISPR effectors may be labeled with binding tags. In certain exemplary embodiments, CRISPR effectors may be chemically tagged. For example, CRISPR effectors may be chemically biotinylated. In other exemplary embodiments, fusions may be created by adding additional sequences encoding the fusion to the CRISPR effector. One example of such a fusion is AviTag®. It uses a method in which a single biotin is attached to a tag consisting of a unique 15 amino acid peptide by a highly targeted enzyme. In certain aspects, the CRISPR effector may be labeled with a capture tag such as GST, Myc, hemagglutinin (HA), green fluorescent protein (GFP), flag, His-tag, TAP-tag, and Fc-tag, although these is not limited to Binding tags, either fusions, chemical tags, or capture tags, may be used to destroy the CRISPR effector system once bound to the target nucleic acid, or to immobilize the CRISPR effector system to a solid substrate surface.

In certain exemplary embodiments, the guide RNA may be labeled with a binding tag. In certain exemplary embodiments, in vitro transcription (IVT) incorporating one or more biotinylated nucleotides (eg, biotinylated uracil) may be used to label the entire guide RNA. In some embodiments, biotin may be chemically or enzymatically added to the guide RNA, such as by adding one or more biotin groups to the 3' end of the guide RNA. After binding has occurred, the binding tag may be used to disrupt the guide RNA/target nucleic acid complex, for example, by exposing the guide RNA/target nucleic acid to a streptavidin-coated solid substrate.

Accordingly, in certain exemplary embodiments, engineered or non-naturally occurring CRISPR effectors may be used for enrichment purposes. In one embodiment, this modification may involve mutation of one or more amino acid residues of the effector protein. Such one or more mutations may be in one or more catalytically active domains of the effector protein. The effector protein may have reduced or no nuclease activity compared to the effector protein lacking one or more mutations. The effector protein may not induce RNA strand cleavage at the target locus of interest. In one preferred aspect, the one or more mutations may comprise two mutations. In one preferred aspect, said one or more amino acid residues are modified in the C2c2 effector protein (eg, an engineered, ie non-naturally occurring effector protein or C2c2). In certain embodiments, the one or more modified mutated amino acid residues are R597, H602, R1278, and H1283 (relative to the Lsh C2c2 amino acid) (e.g., mutations R597A, H602A, R1278A, and H1283A) or the corresponding amino acid residue of the Lsh C2c2 orthologue.

In certain embodiments, the one or more modified mutated amino acid residues are K2, K39, V40, E479, L514, V518, N524, G534, K535, E580, L597, V602, according to the C2c2 consensus numbering. D630, F676, L709, I713, R717 (HEPN), N718, H722 (HEPN), E773, P823, V828, I879, Y880, F884, Y997, L1001, F1009, L1013, Y1093, L1099, L1111, Y1134, L1200 D1222, Y1244, L1250, L1253, K1261, I1334, L1355, L1359, R1362, Y1366, E1371, R1372, D1373, R1509 (HEPN), H1514 (HEPN), Y1543, D1544, K1546, K15548, I15548, V1 One or more amino acid residues of C2c2. In certain aspects, the one or more modified mutated amino acid residues are one or more amino acid residues of C2c2 corresponding to R717 and R1509. In certain aspects, the one or more modified mutated amino acid residues are one or more amino acid residues of C2c2 corresponding to K2, K39, K535, K1261, R1362, R1372, K1546, and K1548. . In certain aspects, the mutation alters or modifies the activity of the protein. In certain aspects, said mutation reduces the activity of the protein, such as reducing specificity. In certain aspects, the mutation abolishes the protein's catalytic activity (ie, "dead" C2c2). In one embodiment, said amino acid residues correspond to Lsh amino acid residues or the corresponding amino acid residues of C2c2 proteins from different species. Equipment that can facilitate these processes.

A specific nucleic acid sample may also be depleted using the enrichment system described above. For example, a guide RNA may be designed to bind to non-target RNA and remove non-target RNA from a sample. In one exemplary embodiment, guide RNAs may be designed to bind to nucleic acids bearing specific nucleic acid diversity. For example, a given sample may be expected to have a high copy number of non-diverse nucleic acids. Thus, the embodiments disclosed herein may be used to remove non-diverse nucleic acids from a sample to increase the efficiency with which a detection CRISPR effector system can detect target variant sequences in a given sample. good.

protein detection

In addition to nucleic acid detection, the systems, devices, and methods disclosed herein may be employed for detection of polypeptides (or other molecules) by specifically configured polypeptide detection aptamers. Polypeptide detection aptamers are distinct from the masking construct aptamers described above. First, aptamers are designed to specifically bind to one or more target molecules. In one exemplary embodiment, the target molecule is a target polypeptide. In other exemplary embodiments, the targeting molecule is a targeting chemical compound, eg, a targeting therapeutic molecule. Methods for designing and selecting aptamers with specificity for a given target (eg, SELEX) are known in the art. In addition to specificity for a given target, aptamers have also been designed to incorporate RNA polymerase promoter binding sites. In certain exemplary embodiments, the RNA polymerase promoter is the T7 promoter. Prior to target binding, the RNA polymerase site is inaccessible or recognizable to the RNA polymerase. However, once the aptamer binds to its target, the aptamer structure undergoes a conformational change that exposes the RNA polymerase promoter. Aptamer sequences downstream of the RNA polymerase promoter serve as templates for the generation of trigger RNA oligonucleotides by RNA polymerase. Thus, the aptamer template portion may further incorporate barcodes or other identifying sequences that identify a given aptamer and its target. The guide RNAs described above may then be designed to recognize these specific trigger oligonucleotide sequences. Binding of the guide RNA to the trigger oligonucleotide activates the CRISPR effector protein to deactivate the masking construct as described above and produce a detectable positive signal.

Thus, in certain exemplary embodiments, the methods disclosed herein dispense a sample or set of samples into a set of discrete volumes (where one or more discrete volumes each comprising a peptide-detecting aptamer, a CRISPR effector protein, one or more guide RNAs, a masking construct), and a sample under conditions sufficient to allow the peptide-detecting aptamer to bind to said one or more target molecules. Include the additional step of incubating the set of samples. Here, when the aptamer binds to the corresponding target, the RNA polymerase promoter binding site is exposed and trigger RNA is synthesized by binding of RNA polymerase to the RNA polymerase promoter binding site.

In other exemplary embodiments, binding of the aptamer may expose a primer binding site when the aptamer binds to the target polypeptide. For example, aptamers may expose RPA primer binding sites. Thus, the addition or inclusion of primers feeds into an amplification reaction, such as the RPA reaction outlined above.

装置 In certain exemplary embodiments, the aptamer may be a conformation-switching aptamer and upon binding the target of interest may change secondary structure to expose new regions of single-stranded DNA. . In certain exemplary embodiments, these new regions of single-stranded DNA can be used as substrates for ligation to extend aptamers and be specifically detected using embodiments disclosed herein. Long ssDNA molecules may be produced. Aptamer design may also be combined with tertiary complexes for detection of low epitope targets (e.g. glucose) (Yang et al. 2015: http://pubs.acs.org/doi/abs/10.1021/acs .analchem.5b01634 ). Examples of conformationally shifting aptamers and corresponding guide RNAs (crRNAs) are shown in Table 7 below.

Device

The systems described herein may be embodied in diagnostic equipment. Multiple substrates and configurations of devices in which multiple discrete volumes can be defined may be used. As used herein, the term “discrete volume” refers to a discrete space such as a container, receptacle, or any other defined volume that can be defined by its property of preventing and/or inhibiting migration of a target molecule. Refers to volume or space. For example, a volume or space defined by a physical property such as a wall (e.g., well, tube wall), or the surface of a droplet, which may be impermeable or semi-permeable, or chemical methods, diffusion rate limiting , electromagnetic methods, light irradiation, or any combination thereof, which may include a target molecule and an indicative nucleic acid identifier (e.g., a nucleic acid barcode). . "Diffusion rate limiting" (e.g., the volume defined by diffusion) means that if there are two parallel laminar flows, diffusion limits the transition of target molecules from one flow to the other, and diffusion By effectively limiting the definition of space or volume, we mean the space available only for certain molecules or reactions. A volume or space defined by a "chemical method" means a space in which only a particular target molecule may reside due to the chemical or molecular properties of that target molecule, eg particle size. For example, gel beads exclude certain species from entering the bead due to surface charge, matrix particle size, or other physical properties of the bead that allow selection of the species that may enter the interior of the bead. , does not exclude other species. Volumes or spaces defined by "electromagnetic methods" can be defined using the electromagnetic properties (e.g. charge or magnetic properties) of the target molecule or its support, e.g. means a space in which a particular region within the space can be defined, such as by supplementing with . An "optically" defined volume is defined by illuminating with visible, ultraviolet, infrared, or other wavelengths of light such that only target molecules within the defined space or volume are labeled. means any region of space that may be One advantage of using a wallless or semi-permeable discrete volume is that some reagents, such as buffers, chemically active agents, or other agents, may pass through the discrete volume, while others, such as target molecules, may pass through the discrete volume. That is, the materials may be maintained in separate volumes or spaces. Typically, the discrete volume is a fluid medium (e.g., aqueous solution, oil, buffer, and/or cell) suitable for labeling target molecules with an indexable nucleic acid identifier under conditions that permit labeling. medium that can support growth). Exemplary discrete volumes or spaces useful in the disclosed methods include droplets (e.g., microfluidic droplets and/or emulsified droplets), hydrogel beads or other polymeric structures (e.g., diacrylic acid polyethylene glycol beads or agarose beads), tissue slides (e.g., fixed formalin paraffin-embedded tissue slides having specific areas, volumes, or spaces defined by chemical, optical, or physical methods), inter alia, Tubes (e.g., centrifuge tubes, microcentrifuge tubes, test tubes, cuvettes, conical tubes, etc.), jars (e.g., glass, plastic, ceramic jars) containing reagents in a regular array or random pattern , Erlenmeyer flasks, scintillation vials, etc.), wells (eg, the wells of a plate), plates, pipettes, microscope slides with areas defined by placing pipette tips. In certain aspects, the compartments are aqueous droplets in a water-in-oil emulsion. In certain embodiments, any of the applications, methods, or systems described herein that require accurate or uniform volumes may employ acoustic liquid dispensers.

In certain exemplary embodiments, the device includes a substrate of flexible material on which a plurality of spots may be defined. Flexible material substrates suitable for use in diagnostics and biosensing are known in the art. Flexible substrate materials may be made of plant-derived fibers (eg, cellulose fibers) or flexible polymers (eg, flexible polyester films and other types of polymers). good. Add reagents to individual spots within each defined spot of the system described herein. Each spot may contain the same reagents except that the guide RNA or set of guide RNAs is different, or may contain different detection aptamers for sorting multiple targets at once, if applicable. . Thus, the systems and devices herein can screen samples from multiple sources (e.g., multiple clinical samples from different individuals) for the presence of the same target or a limited number of targets, or samples It may be possible to screen portions of a sample (or multiple samples from the same source) for the presence of multiple different targets in the sample. In certain exemplary embodiments, the elements of the systems described herein are freeze-dried on paper or cloth substrates. Examples of substrates composed of flexible materials that may be used in certain exemplary devices are described in Pardee et al. Cell. 2016, 165(5):1255-66 and Pardee et al. Cell. 4):950-54. Substrates of flexible materials suitable for use with bodily fluids, including blood, are disclosed in International Patent Application Publication No. WO/2013/071301 to Shevkoplyas et al. U.S. Patent Application Publication No. 2011/0111517 to Siegel et al. (titled "Paper-based microfluidic systems"), and Siegel et al. Shafiee et al. “Paper and Flexible Substrates as Materials for Biosensing Platforms to Detect Multiple Biotargets,” Scientific Reports 5:8719 (2015), further , for flexible materials, including materials suitable for use in wearable diagnostic devices, see “Flexible Substrate-Based Devices for Point-of-Care Diagnostics.” )” Cell 34(11):909-21 (2016). Additionally, the flexible material may include nitrocellulose, polycarbonate, methylethylcellulose, polyvinylidene fluoride (PVDF), polystyrene, or glass (see, eg, US 20120238008). In certain aspects, the discrete volumes are separated by hydrophobic surfaces such as, but not limited to, wax, photoresist, or solid ink.

In some embodiments, a dosimeter or badge may be provided that acts as a sensor or indicator such that the wearer is informed of exposure to specific microorganisms or other agents. For example, the systems described herein may be used to detect specific pathogens. Similarly, the aptamer-based embodiments disclosed above may be used to detect both polypeptides and other agents (eg, chemical agents) to which a particular aptamer may bind. Such devices can be used by soldiers or other military personnel, clinicians, and researchers to provide information as quickly as possible about exposure to potentially dangerous microbes, for example, for the detection of biological or chemical warfare agents. , hospital staff, etc. In other embodiments, such visitor badges may be used to protect immunocompromised patients, burn patients, patients undergoing chemotherapy, children, or the elderly from exposure to dangerous microbes or pathogens. .

Sources of samples that may be analyzed using the systems and devices described herein include subject biological or environmental samples. Environmental samples may include surfaces or fluids. Biological samples include, but are not limited to, saliva, blood, plasma, serum, faeces, urine, saliva, mucus, lymph, synovial fluid, spinal fluid, cerebrospinal fluid, skin or mucosal swabs, or combinations thereof. may contain. In one exemplary embodiment, environmental samples are taken from solid surfaces (eg, surfaces used in food preparation) or other sensitive compositions and materials.

In other exemplary embodiments, the elements of the systems described herein may rest on disposable substrates used to wipe surfaces or sample fluids, such as swabs or cloths. For example, the system can be used to test for the presence of pathogens on food surfaces such as fruits or vegetables by swabbing them. Similarly, this disposable substrate may be used to wipe other surfaces for detection of specific microorganisms or agents (eg, for use in security screening). This disposable substrate may also have forensic applications. In this case, the CRISPR system may be used, for example, to identify DNA SNPs that may be used to identify a suspect, or to detect specific tissue or cell markers that determine the biological material present in a sample. Designed. Similarly, the disposable substrate may be used to collect samples from patients (eg, saliva samples from the mouth or swabs from the skin). In other embodiments, a sample or swab may be taken from the meat product to detect contaminants on or within the meat product.

There is a need for near real-time microbial diagnostics in food, clinical, industrial, and other settings (e.g., Lu TK, Bowers J, and Koeris MS., Trends Biotechnol. 2013 Jun;31(6):325 -7). In certain aspects, food-borne pathogens (e.g., Campylobacter jejuni, Clostridium perfringens, Salmonella, Escherichia coli, Bacillus cereus, Listeria monocytogenes, Shigella) using pathogen-specific guide RNAs Genus Yellow Staphylococcus, Staphylococcal enteritis, Streptococcus, Vibrio cholerae, Vibrio parahaemolyticus, Vibrio vulnificus, Yersinia enterocolitica and Yersinia pseudotuberculosis, Brucella, Corynebacterium Ulcerans, Coxiella burnetii, or Plesiomonas shigeroides) is used for the rapid detection.

In certain embodiments, the device is or includes a flow strip. For example, horizontal flow strips can detect RNases (eg, C2c2) by color. The RNA reporter is modified to have a first molecule (e.g. FITC) attached to the 5' end and a second molecule (e.g. biotin) attached to the 3' end (or vice versa). A horizontal flow strip is designed with two capture lines, an anti-first molecule (eg, anti-FITC) antibody is hybridized to the first line and an anti-second molecule (eg, anti-biotin) antibody is hybridized to the first line. Hybridized to a second downstream line. As the SHERLOCK reaction flows through the strip, the uncleaved reporter binds to the anti-first molecule on the first capture line and the cleaved reporter releases the second molecule to bind to the second molecule on the second capture line. combine with The second molecule binds to any second molecule in the first or second line, e.g., sandwiching antibodies bound to nanoparticles (e.g. gold nanoparticles), resulting in a strong output/signal (e.g. , color) are generated. As more reporters are cleaved, more signal accumulates in the second capture line and less signal appears in the first line. In certain aspects, the invention relates to the use of the Followstrips described herein to detect nucleic acids or polypeptides. In a particular aspect, the invention relates to a method of detecting nucleic acids or polypeptides with a flow strip as defined herein, for example in a (lateral) flow test or (lateral) flow immunochromatographic assay.

In certain exemplary embodiments, the device is a microfluidic device that generates and/or merges different droplets (ie discrete volumes). For example, a first set of droplets may be formed containing the sample to be sorted, and a second set of droplets may be formed containing the elements of the systems described herein. The first set of droplets and the second set of droplets are then merged and the diagnostic methods described herein are performed on the merged set of droplets. The microfluidic devices disclosed herein may be silicon chips and may be fabricated using a variety of techniques. Such techniques include, but are not limited to, thermal embossing, elastomer molding, microinjection, LIGA (Lithographie, Galvanoformung, Abformung), soft lithography, silicon forming, and related thin film processing techniques. . Materials suitable for making microfluidic devices include, but are not limited to, cyclic olefin copolymers (COC), polycarbonate, polydimethylsiloxane (PDMS), and polymethyl acrylate (PMMA). In one aspect, soft lithography of PDMS may be used to fabricate microfluidic devices. For example, photolithography may be used to create molds that define the locations of flow channels, valves, filters within the matrix. The matrix material is poured into a mold and allowed to harden to produce a stamp. The stamp is then applied to a solid support, such as but not limited to glass. Because some polymers, such as PDMS, are hydrophobic, passivating agents may be necessary, as some proteins can absorb them and interfere with certain biological processes (Schoffner et al. Nucleic Acids). Research, 1996, 24:375-379). Suitable passivating agents are known in the art and include, but are not limited to silanes, parylenes, n-dodecyl-bD-maltoside (DDM), Pluronics, Tween-20 and other similar surfactants. , polyethylene glycol (PEG), albumin, collagen, and other similar proteins and peptides.

In certain exemplary embodiments, systems and/or devices may be used to convert flow cytometry readouts. Alternatively, it can be used to enhance existing flow-based methods (eg, PrimeFlow assay) with sensitive quantitative measurements of 1 million cells in a single experiment. In certain exemplary embodiments, cells may be placed in droplets containing unpolymerized gel monomers, which are then placed in single cell droplets suitable for analysis by flow cytometry. Droplets containing unpolymerized gel monomers may contain detection constructs containing fluorescent detectable labels. Polymerization of the gel monomers forms beads within the droplets. Since gel polymerization is driven by free radical formation, fluorescent reporters are covalently attached to the gel. This detection construct may be further modified to include a linker (eg, an amine). A quencher may be added after gel formation and attached to the reporter construct via a linker. The quencher is therefore not bound to the gel and is free to diffuse upon cleavage of the reporter by the CRISPR effector protein. Detection constructs and hybridization chain reaction (HCR inhibitor) amplification may be combined to achieve droplet signal amplification. DNA/RNA hybrid hairpins may be incorporated into gels, which may include hairpin loops with RNase-sensitive domains. By protecting the strand displacement scaffolding within the hairpin loop with an RNase-sensitive domain, the HCR initiator may be selectively deprotected after the hairpin loop is cleaved by the CRISPR effector protein. After deprotection of the HCR initiator by strand displacement via the scaffolding sequence, the fluorescent HCR monomers can be washed and loaded onto the gel for inhibitor deprotected signal amplification.

An example of a microfluidic device that may be used in the context of the present invention is described in Hou et al. "Direct Detection and drug-resistance profiling of bacteremias using inertial microfluidics." )” Lap Chip. 15(10):2297-2307 (2016).

The system described herein further includes a wearable device that assays a subject's biological sample (e.g., bodily fluid) outside of a clinic setting and reports the results of the assay remotely to a central server accessible to a physician. It may be incorporated into a medical device. The device may include the ability to self-collect blood; Blood Sampling”) and US Patent Application Publication No. 2015/0065821 to Andrew Conrad entitled “Nanoparticle Phoresis”.

In certain exemplary embodiments, the device may include individual wells, such as macroplate wells. Macroplate well sizes may be standard 6, 24, 96, 384, 1536, 3456, or 9600 wells. In certain exemplary embodiments, the elements of the systems described herein may be freeze-dried and applied to the surfaces of the wells prior to distribution and use.

The devices disclosed herein may further include inlets and outlets, or openings, which are valves, tubes, channels, chambers, and syringes, for introducing/removing fluids to/from the device. and/or may be connected to a pump. The device may be coupled with a fluid flow actuator that enables directional movement of fluid within the microfluidic device. Examples of actuators include, but are not limited to, syringe pumps, mechanically actuated recirculation pumps, electroosmotic pumps, balls, bellows, diaphragms, or air bubbles intended to move fluid. In certain exemplary embodiments, the device is linked to a controller by programmable valves that act together to move fluid through the device. In certain exemplary embodiments, the device is linked to a controller, which is described in more detail below. The device may be connected to the flow actuator, controller and sample loading device by a metal pinned tube that is inserted into the inlet of the device.

As shown herein, the elements of the system are stable when freeze-dried. Accordingly, embodiments that do not require a support device are also envisioned. That is, the system may be applied to any surface or fluid bearing reaction solution disclosed herein and detect a detectable positive signal from that surface or solution. In addition to freeze-drying, the system may also be stably stored and used in the form of pellets. Polymers useful in forming suitable pellet forms are known in the art.

In certain aspects, a CRISPR effector protein is associated with each individual volume of the device. Each separate volume may contain a different guide RNA specific for a different target molecule. In certain aspects, the sample may be exposed to a solid substrate containing two or more separate volumes each containing guide RNA specific for a target molecule. Without being bound by any theory, each guide RNA captures its target molecule from the sample, eliminating the need to split the sample into separate assays. Therefore, useful samples may be preserved. The effector protein may be a fusion protein containing an affinity tag. Affinity tags are well known in the art (eg, HA tag, Myc tag, Flag tag, His tag, biotin). Effector proteins may be conjugated to biotin molecules and separate volumes may contain streptavidin. In other embodiments, the CRISPR effector protein is conjugated to an antibody specific for the effector protein. Methods for conjugating CRISPR enzymes are described above (see, eg, US20140356867A1).

The devices disclosed herein may also include elements of point-of-care (POC) devices known in the art that otherwise sample. See, e.g., St John and Price, "Existing and Emerging Technologies for Point-of-Care Testing" (Clin Biochem Rev. 2014 Aug; 35(3): 155-167). matter.

The present invention may also be used with wireless lab-on-chip (LOC, small gene analysis) diagnostic sensor systems (see, for example, US Pat. No. 9,470,699, "Diagnostic radio frequency identification sensors and applications thereof"). Radio Frequency Identification Sensors for Diagnostics and Their Applications)”). In certain aspects, the invention is implemented at a LOC controlled by a wireless device (eg, mobile phone, personal digital assistant (PDA), tablet) and results are reported to the device.

Radio frequency identification (RFID) tag systems include RFID tags that transmit data that are received by an RFID reader (also called interrogator). In a typical RFID system, individual objects (eg, items in a store) are equipped with relatively small tags containing transponders. A transponder has a memory chip with a unique electronic product code. The RFID reader emits a signal that activates the transponder in the tag through the use of communication test protocols. Thus, an RFID reader can read data from and write data to the tag. The RFID tag reader also processes the data according to the application of the RFID tag system. Currently there are passive and active RFID tags. Passive RFID tags do not contain an internal power source, but are powered by radio frequency signals received from an RFID reader. Alternatively, an active RFID tag includes an internal power source that can power the active RFID tag, has a wide transmission range and a large memory capacity. Whether to use passive or active tags depends on the particular application.

Lab-on-a-chip technology is well documented in the scientific literature and consists of multiple microfluidic channels, inputs, or chemical wells. Radio frequency identification (RFID) tag technology may be used to measure the reactions in the wells. This is because conductive leads from the RFID electronic chip may be directly connected to each of the test wells. Antennas are printed or mounted on other layers of the electronic chip or directly on the back of the device. Additionally, leads, antennas, and electronic chips may be embedded in the LOC chip, which can prevent shorting of electrodes or electronics. LOC enables separation and analysis of complex samples, and this technique allows LOC testing independent of complex or expensive readers. Rather, a simple wireless device (eg, cell phone or PDA) may be used. In one aspect, the wireless device also controls the separation and control of microfluidic grooves with more complex LOC analysis. In one aspect, LEDs and other electronic measuring or sensing devices are included in the LOC-RFID chip. Without being bound by any theory, this technology is disposable and allows complex tests requiring separation and mixing to be performed outside the laboratory.

In preferred embodiments, the LOC may be a microfluidic device. The LOC may be a passive chip, said chip being activated and controlled by the wireless device. In certain aspects, the LOC includes microfluidic channels to hold reagents and channels to introduce samples. In certain aspects, a signal from the wireless device delivers power to the LOC to activate mixing of the sample and assay reagents. Specifically, for the present invention, the system may comprise a masking factor, a CRISPR effector protein, and a guide RNA specific for the target molecule. When the LOC is activated, the microfluidic device may mix the sample and assay reagents. Once mixed, the sensor detects the signal and transmits the result to the wireless device. In certain aspects, the unmasking agent is a conducting RNA molecule. A conductive RNA molecule may be attached to a conductive material. Conductive molecules may be conductive nanoparticles, conductive proteins, metal particles attached to proteins, or conductive latex or other beads. In certain aspects, when using DNA or RNA, the conductive molecule may be attached directly to the corresponding DNA or RNA strand. When the conductive molecule is released, it may be detected by a sensor. The assay may be a one-step process.

The ability to measure surface area conductivity enables accurate quantitative results in disposable wireless RFID electronic assays. Furthermore, since the test area is very small, more tests can be performed in a given area, thus saving costs. In certain embodiments, each individual sensor is associated with a different CRISPR effector protein and guide RNA immobilized on the sensor and used to detect multiple target molecules. Without wishing to be bound by any theory, the operation of different sensors may be distinguished by the wireless device.

In addition to the conductive methods described herein, other methods relying on RFID or Bluetooth may be used as a low base cost communication and power platform for disposable RFID assays. For example, optical means may be used to test for the presence and concentration of a given target molecule. In certain aspects, the optical sensor detects unmasking of the fluorescent masking agent.

In certain embodiments, the devices of the invention comprise portable handheld assay diagnostic readers (e.g. Vashist et al., Commercial Smartphone-Based Devices and Smart Applications for Personalized Healthcare Monitoring and Management, Diagnostics 2014, 4(3 ), 104-128; mReader from Mobile Assay; and Holomic Rapid Diagnostic Test Reader).

As shown herein, certain embodiments are particularly useful when using the embodiments in POC situations and/or resource-poor environments where access to more complex detection equipment for signal readout may be limited. Detection is possible by a colorimetric change with attendant benefits. However, the portable embodiments disclosed herein may also be coupled with portable spectrophotometers capable of detecting signals outside the visible light range. An example of a portable spectrophotometer device that may be used in conjunction with the present invention is Das et al. "Ultra-portable, wireless smartphone spectrophotometer for rapid, non-destructive testing of fruit ripeness." 2016, 6:32504, DOI: 10.1038/srep32504. Finally, in certain embodiments using quantum dot-based masking constructs, the signal can be successfully detected using a portable UV light device or other suitable device due to the near-perfect quantum yield provided by the quantum dots. There is

Exemplary methods and assays

The assay platform is low-cost and adaptable for (i) universal RNA/DNA/protein quantification, (ii) rapid multiplex detection of RNA/DNA and protein expression, and (iii) targets in clinical and environmental samples. Suitable for multiple applications including sensitive detection of nucleic acids, peptides and proteins. The systems disclosed herein may also be used to detect transcripts within biological settings such as cells. Given the highly specific nature of the CRISPR effectors described herein, it may be possible to follow allele-specific expression of transcripts or disease-associated mutations in living cells.

In certain exemplary embodiments, one guide RNA specific for one target is contained in separate volumes. Each volume may then receive a different sample or portion thereof of the same sample. In certain exemplary embodiments, multiple guide RNAs for individual targets may each be placed in one well such that multiple targets are sorted in different wells. Multiple effector proteins with different specificities may be used to detect multiple guide RNAs within one volume in certain exemplary embodiments. For example, different orthologues with different sequence specificities may be used. For example, some orthologs preferentially cleave A, while other orthologs preferentially cleave C, U, or T. Thus, guide RNAs containing all or substantially a portion of one nucleotide may be generated each with a different fluorophore. Thus four different targets may be sorted in one separate volume.

As indicated above, the CRISPR effector system can detect attomolar concentrations of target molecules. See, eg, FIGS. 13, 14, 19, 22 and the examples described below. Due to the sensitivity of the system, multiple applications requiring fast and sensitive detection may benefit from the embodiments disclosed herein and are envisioned within the scope of the present invention. Exemplary assays and uses are described in further detail below.

Application to microorganisms

In certain exemplary embodiments, the systems, devices, and methods disclosed herein detect the presence of one or more microbial agents in a sample (e.g., a biological sample obtained from a subject). Regarding. In certain exemplary embodiments, the microorganism may be a bacterium, fungus, yeast, protozoan, parasite, or virus. Thus, the methods disclosed herein are useful for rapid identification of microbial species, monitoring the presence of microbial proteins (antigens), antibodies, antibody genes, detecting specific phenotypes (e.g., bacterial resistance), disease progression and /or may be used in (or in combination with) other methods of application in conjunction with pandemic surveillance and other methods requiring antibiotic selection. Due to the rapid and sensitive diagnostic capabilities of the embodiments disclosed herein, the detection of microbial species with a single nucleotide difference, and the ability to deploy as a POC device, using the embodiments disclosed herein , may guide treatment regimens such as selection of appropriate antibiotics or antiviral agents. Embodiments disclosed herein may be used to screen environmental samples (air, water, surfaces, food, etc.) for the presence of microbial contamination.

Disclosed are methods of identifying microbial species (eg, species such as bacteria, viruses, fungi, yeast, or parasites). Certain embodiments disclosed herein describe methods and systems that can identify and differentiate microbial species to recognize many different microorganisms in a single sample or across multiple samples. The methods of the invention detect a pathogen in a sample by detecting the presence of a target nucleic acid sequence in a biological or environmental sample and detect one or more organisms (e.g., bacterial viruses, yeast, protozoa, and fungi, or combinations thereof) can be distinguished. A positive signal obtained from the sample indicates the presence of microorganisms. Multiple microorganisms can be identified simultaneously using more than one effector protein using the methods and systems of the present invention. Here, each effector protein targets a specific microbial target sequence. In this way, a multi-level assay that can detect any number of microorganisms at once may be performed on a particular subject. In some embodiments, multiple microorganisms may be detected simultaneously using a set of probes capable of identifying one or more microbial species.

Multiplex analysis of samples allows for large scale detection of samples, reducing the time and cost of analysis. However, multiplex analysis is often limited by the availability of biological samples. However, according to the present invention, an alternative method to multiplex analysis may be performed, such as adding multiple effector proteins to one sample and each masking construct is bound to a separate quencher dye. In this case, a positive signal may be obtained from each quencher dye separately for multiple detections in one sample.

Methods are disclosed for distinguishing between two or more species of one or more organisms in a sample. The method is also suitable for detecting one or more species of one or more organisms in a sample.

Microorganism detection

In some embodiments, methods of detecting microorganisms in a sample are provided. The method includes dispensing a sample or set of samples into one or more discrete volumes containing a CRISPR system described herein; incubating the sample or set of samples under conditions sufficient for the guide RNA to bind; allowing the binding of the one or more guide RNAs to one or more target molecules to activate the CRISPR effector proteins. (where activation of the CRISPR effector protein modifies the RNA-based masking construct such that a detectable positive signal is produced); and detecting the detectable positive signal (where detection Detection of a possible positive signal indicates the presence of one or more target molecules in the sample). The one or more target molecules may be mRNA, gDNA (coding or non-coding), trRNA, or RNA containing a target nucleotide sequence that may be used to distinguish two or more microbial species/strains from each other. good. A guide RNA may be designed to detect a target sequence. Embodiments disclosed herein may also employ certain steps to enhance the hybridization of guide RNA and target RNA sequences. Methods for enhancing ribonucleic acid hybridization are disclosed in WO2015/085194, entitled "Enhanced Methods of Ribonucleic Acid Hybridization", the contents of which are incorporated herein by reference. . Microorganism-specific targets may be RNA or DNA or proteins. For DNA, the method may further comprise the use of DNA primers that introduce the RNA polymerase promoters described herein. When the target is a protein, the method uses aptamers and processes specific for protein detection as described herein.

Detection of single nucleotide variants

In some embodiments, one or more of the identified target sequences may be detected using guide RNAs that are specific for and bind to the target sequences described herein. The systems and methods of the present invention can distinguish even single nucleotide polymorphisms present in different microbial species, thus the use of multiple guide RNAs according to the present invention can be used to distinguish between species. Good target sequences may be further expanded or improved. For example, in some embodiments, one or more guide RNAs may distinguish microorganisms by species, genus, family, order, class, phylum, kingdom, phenotype, or a combination thereof.

Detection based on rRNA sequence

In certain exemplary embodiments, the devices, systems, and methods disclosed herein may be used to distinguish between multiple microbial species in a sample. In certain exemplary embodiments, identification may be based on ribosomal RNA sequences containing the 16S, 23S, and 5S subunits. Methods for identifying related rRNA sequences are disclosed in US Patent Application Publication No. 2017/0029872. In certain exemplary embodiments, the set of guide RNAs may be designed to distinguish species by species or strain-specific variable regions. Guide RNAs may also be designed against target RNA genes that distinguish microorganisms by genus, family, order, class, phylum, kingdom, or combinations thereof. In certain exemplary embodiments where amplification is used, the set of amplification primers is designed to flanking constant regions of the ribosomal RNA sequence, and the guide RNA may be designed to distinguish between species by internal variable regions. good. In certain exemplary embodiments, the primers and guide RNA may each be designed against the conserved variable region of the 16S subunit. Other genes or genomic regions that vary uniquely across species or subsets of species (eg, RecA gene family, RNA polymerase β subunit) may be used. Other suitable phylogenetic markers and methods of identifying them are described, for example, in Wu et al. arXiv:1307.8690 [q-bio.GN].

In certain exemplary embodiments, methods or diagnostics may be designed to sort microorganisms across multiple phylogenetic and/or phenotypic levels simultaneously. For example, a method or diagnosis may involve using multiple CRISPR systems with different guide RNAs. The first set of guide RNAs may, for example, distinguish between Mycobacterium, Gram-positive and Gram-negative bacteria. These general classes may be further subdivided. For example, a guide RNA that distinguishes between enteric and non-enteric within Gram-negative bacteria may be designed and used in the method or diagnosis. A second set of guide RNAs may be designed to distinguish microorganisms at the genus or species level. Thus, a matrix is generated to contain Mycobacterium, Gram-positive and Gram-negative bacteria (also enteric and enteric) with each genus of bacterial species within one of these classes identified in a given sample. divided into non-enteric) may be identified. The above is for example only for these purposes. Other means of classifying other microbial species are also envisioned and follow the general structure above.

Screening for drug resistance

In certain exemplary embodiments, the devices, systems, and methods disclosed herein may be used to screen for microbial genes of interest (eg, antibiotic and/or antiviral drug resistance genes). Guide RNAs may be designed to distinguish between known genes of interest. Samples, including clinical samples, may then be screened using embodiments disclosed herein for detection of such genes. The ability to screen for drug resistance in POC is of great benefit in selecting appropriate treatment regimens. In certain exemplary embodiments, the antibiotic resistance gene is a carbapenemase, including KPC, NDM1, CTX-M15, OXA-48. Other antibiotic resistance genes are known, see, for example, the Comprehensive Antibiotic Resistance Database (Jia et al. “CARD 2017: expansion and model-centric curation of the Comprehensive Antibiotic Resistance Database”). Development of substance resistance databases and curation centered on models).” Nucleic Acids Research, 45, D566-573).

Ribavirin is a potent antiviral agent that attacks multiple RNA viruses. Several clinically important viruses have developed ribavirin resistance. Examples of such include foot-and-mouth disease virus doi:10.1128/JVI.03594-13; poliovirus (Pfeifer and Kirkegaard. PNAS, 100(12):7289-7294, 2003); Virol. 79(4):2346-2355, 2005). Several other resistant RNA viruses (e.g. hepatitis and HIV) have developed resistance to existing antiviral drugs: hepatitis B virus (lamivudine, tenofovir, entecavir) doi: 10/1002/hep22900; hepatitis C virus (telaprevir, BILN2061, ITMN-191, SCh6, boceprevir, AG-021541, ACH-806) doi: 10.1002/hep.22549; and HIV (many drug resistance mutations) hivb.standford.edu. Embodiments disclosed herein may be used to detect such variants, among others.

Apart from drug resistance, there are multiple clinically relevant mutations that can be detected with the embodiments disclosed herein. For example, resistant viral acute infections of LCMV (doi:10.1073/pnas.1019304108), and increased infectivity of Ebola (Diehl et al. Cell. 2016, 167(4):1088-1098).

As described elsewhere herein, closely related microbial species (e.g., with a single nucleotide difference at a given target sequence) may be distinguished by the introduction of synthetic mismatches into the gRNA. .

set cover method

In certain embodiments, a set of guide RNAs is designed, for example, to allow identification of all microbial species within a defined set of microorganisms. Such methods are described in certain exemplary embodiments, and methods for generating the guide RNAs described herein are disclosed in WO2017/040316 (incorporated herein by reference). can be compared with As described in WO2017040316, population coverage solves the minimum number of target sequence probes or guide RNAs required to cover the entire target sequence or set of target sequences (e.g., set of genomic sequences). may be identified. Traditionally, aggregate coverage methods have been used to identify primers and/or microarray probes typically in the 20-50 base pair range. See, for example: Pearson et al., cs.virginia.edu/~robins/papers/primers_dam11_final.pdf., Javado et al. Nucleic Acids Res. 2006 34(22):6605-11, Javado et al. 2008, 36(1):e3 doi10.1093/nar/gkm1106, Duitama et al. Nucleic Acids Res. 2009, 37(8):2483-2492, Phillippy et al. BMC Bioinformatics. 2009, 10 :293 doi:10.1186/1471-2105-10-293. However, such methods generally involved treating each primer/probe as a k-mer to search for exact matches, or using suffix arrays to allow for imprecise matches. . Also, these methods generally require that only one primer or probe bind to each input sequence, and the hybridization is accomplished by choosing primers or probes such that binding positions along this sequence are inappropriate. We take the binomial method to detect . An alternative method may be to partition the target genome into predefined windows, effectively treating each window as a separate input sequence in the binomial method. That is, these methods determine whether a given probe or guide RNA binds inside each window and require that all windows bind to the beginning of the probe or guide RNA. These methods effectively treat each element of the "universe (data set)" in the set coverage problem as either the entire input sequence or the input sequence of a predefined window, each element representing a probe or guide RNA. An initiation is considered "covered" if it is bound within an element. Different probe or guide RNA designs will cover a given target sequence, but these methods limit the flexibility for this design.

In contrast, embodiments disclosed herein relate to detecting long probes or guide RNAs, eg, with lengths in the range of 70 bp to 200 bp suitable for hybrid selection sequencing. The methods disclosed in WO2017/040316 can also be applied herein to identify and facilitate detection sequencing of sequences of all species and/or strains of large and/or variable target sequence sets. A pan-target sequence approach may be taken in which a set of guide RNAs can be defined. For example, the methods disclosed herein may be used to identify all variants of a given virus, or multiple different viruses in a single assay. In addition, the methods disclosed herein treat each element of the "universe" in the set coverage problem as a nucleotide of the target sequence such that the probe or guide RNA binds to some segment of the target genome containing that element. Each element is considered "coated" as long as it is covered. These types of population coverage methods may be used in place of traditional binomial methods, and the methods disclosed herein provide guidance on how probes or guide RNAs hybridize to target sequences. A better model. Hybridization in which the probe or guide RNA binds to one or more target sequences using these methods rather than just asking whether a given guide RNA sequence binds to a given window. Patterns may be detected. From these hybridization patterns, the minimum number of probes or Determine the guide RNA. These hybridization patterns may be determined by defining specific parameters that minimize the loss function, thereby varying the parameters in each species (e.g., to reflect the diversity of each species). Also, minimal probe or guide RNA sets can be identified in a computationally efficient manner. Computational efficiency cannot be achieved by direct application of the set-covering solution as traditionally applied in the context of probe or guide RNA design.

The ability to detect abundance of multiple transcripts may allow the generation of unique microbial signatures that exhibit particular phenotypes. Various machine learning techniques may be used to generate genetic signatures. Thus, CRISPR-based guide RNAs may be used to identify and/or quantify the relative abundance of biomarkers defined by genetic signatures to detect specific phenotypes. In certain exemplary embodiments, the genetic signature indicates susceptibility to antibiotics, resistance to antibiotics, or a combination thereof.

In one aspect of the invention, the method includes detecting one or more pathogens. In this way, differentiation of a subject's infection by individual microorganisms may be obtained. In some embodiments, such distinctions may allow clinicians to detect or diagnose specific diseases (eg, different variants of the disease). Preferably, the pathogen sequence is the genome of the pathogen or a fragment thereof. The method may further comprise determining pathogen evolution. Determining pathogen evolution may include identifying pathogen mutations, eg, nucleotide deletions, nucleotide insertions, nucleotide substitutions, and the like. Among the latter are non-synonymous substitutions, synonymous substitutions, and non-coding substitutions. Mutations are often non-synonymous during development. The method may further comprise determining the substitution rate between the two pathogen sequences analyzed as described above. However, whether a mutation is deleterious or adaptive requires functional analysis, and the rate of nonsynonymous mutations suggests that the continuation of this epidemic's progression may provide an opportunity for pathogen adaptation. , emphasizing the need for rapid containment. Accordingly, the method may further comprise assessing the risk of viral adaptation and the number of non-synonymous mutations determined (Gire, et al., Science 345, 1369, 2014).

Microbial development monitoring

In some embodiments, the CRISPR system or methods of use thereof described herein may be used to determine the evolution of pathogen development. The method may involve one or more target sequences derived from multiple samples from one or more subjects. Here, said target sequence is a sequence from an outbreak-causing microorganism. Such methods may further comprise determining the transmission pattern of the pathogen or the reaction mechanisms involved in the development of disease caused by the pathogen.

Pathogen transmission patterns include continued new infections or subject-to-subject transmission (e.g., human-to-human transmission) from the natural source of the pathogen, followed by a single infection from the natural source or It may be a mixture of both. In one aspect, the pathogenic transmission may be bacterial or viral, and in such cases the target sequence is preferably the microbial genome or a fragment thereof. In one aspect, the pathogen transmission pattern is the initial pattern of pathogen transmission, ie, the beginning of a pathogen pandemic. Determining a pathogen's transmission pattern at the onset of an outbreak increases the likelihood of stopping the outbreak in the earliest possible time, thereby reducing the potential for regional and international dissemination.

Determining a pathogen's transmission pattern may comprise detecting pathogen sequences by the methods described herein. Determination of pathogen transmission patterns detects intra-host diversity of shared pathogen sequences among subjects and determines whether intra-host diversity of shared pathogen sequences exhibits a temporal pattern. It may further include Patterns of intra- and inter-host variability provide important insights into transmission and epidemiology (Gire, et al., 2014).

Detection of shared intrahost diversity among subjects exhibiting temporal patterns indicates chains of transmission among subjects (especially humans). This is because this can be caused by subject infection from multiple sources (superinfection), sample contamination that repeatedly induces mutations (with or without balanced selection to enhance mutations), or transmission chains. It can be explained by a slightly different virus caused by early mutation (Park, et al., Cell 161(7):1516-1526, 2015). Detecting shared intra-host diversity among subjects may include detecting intra-host variants at common single nucleotide polymorphism (SNP) positions. Positive detection of intrahost variants at common (SNP) positions indicates superinfection and contamination as the main explanation for intrahost variants. Superinfection and contamination can be separated based on SNP frequencies that appear as host-to-host variants (Park, et al., 2015). Otherwise, superinfection and contamination can be ruled out. In the latter case, the detection of shared intrahost diversity among subjects is further enhanced by assessing the frequencies of synonymous and non-synonymous variants and comparing the frequencies of synonymous and non-synonymous variants with each other. may contain. Non-synonymous mutations are mutations that cause amino acid changes in proteins that result in microbial biological changes that result in natural selection. A synonymous substitution does not change the amino acid sequence. The same frequency of synonymous and non-synonymous variants indicates that intra-host variant evolution is neutral. When synonymous and non-synonymous variants differ in frequency, intrahost variants are likely maintained by balanced selection. A low frequency of synonymous and non-synonymous variants indicates recurrent mutations. A high frequency of synonymous and non-synonymous variants indicates co-infection (Park, et al., 2015).

Like Ebola virus, Lassa virus (LASV) can cause hemorrhagic fever and has a very high case-fatality rate. Andersen et al. generated a genome catalog of nearly 200 LASV sequences from clinical and rodent source samples (Andersen, et al., Cell Volume 162, Issue 4, p 738-750, 13 August 2015). ). Andersen et al. show that the 2013-2015 EVD outbreak was fueled by human-to-human transmission, whereas LASV infections were primarily the result of source-to-human transmission. Andersen et al. have elucidated that the spread of LASV across West Africa has been accompanied by changes in LASV genome abundance, mortality, codon adaptation, and translational efficiency. The method includes phylogenetically comparing a first pathogen sequence to a second pathogen sequence and determining whether the first pathogen sequence and the second pathogen sequence are phylogenetically related. It may further include The second pathogen sequence may be the initial reference sequence. If there is a phylogenetic link, the method may further comprise ascertaining the phylogeny of the first pathogen sequence to the second pathogen sequence. This allows the construction of a phylogeny of primary pathogen sequences (Park, et al., 2015).

The method may further comprise determining whether the mutation is deleterious or adaptive. Deleterious mutations represent viral and dead-end infections that are compromised by transmission and are usually present only in individual subjects. Mutations that are unique to an individual subject are those that occur in the terminal branches of the phylogenetic tree, while mutations in the inner branches are mutations that are present in multiple samples (ie, multiple subjects). High nonsynonymous substitution rates are specific to the terminal branches of the phylogenetic tree (Park, et al., 2015).

The inner branches of the phylogenetic tree have increased selection opportunities to remove deleterious mutants. By definition, inner branches give rise to multiple progeny lineages, making them less likely to contain mutations with adaptive costs. Therefore, low nonsynonymous substitution rates indicate an inner branch (Park, et al., 2015).

Synonymous mutations appear to have less impact on adaptation, but occur with more equal frequency in medial and terminal branches (Park, et al., 2015).

By analyzing sequenced target sequences (eg, viral genomes), it is possible to discover mechanisms responsible for the severity of infectious outbreaks, such as in the 2014 Ebola outbreak. For example, Gire et al. phylogenetically compared the 2014 pandemic genome to all 20 genomes from previous pandemics. This comparison suggests that the 2014 West African virus appears to have spread from Central Africa within the past decade. Determining phylogeny using divergences from other Ebolavirus genomes has been problematic (6, 13). However, tracking the oldest outbreak trees revealed a strong correlation between sample date and root-to-tip distance, with a replacement rate of 8×10 ⁻⁴ per site per year (13). . This suggests that all three most recent outbreak lineages diverged from a common ancestor around the same time, around 2004. This supports the hypothesis that each outbreak represents an independent zoonotic event derived from the same genetically distinct virus population in natural sources. They also found that the 2014 EBOV outbreak was caused by a single transmission from a natural source, followed by human-to-human transmission during the outbreak. These results also suggest that the epidemic in Sierra Leone resulted from the introduction of two genetically distinct viruses from Guinea around the same time (Gire, et al., 2014). .

In particular, human-to-human transmission and tracing the history of this spread back 400 years have made it possible to determine how Lassa virus spread from its origin (Andersen, et al., Cell 162). (4):738-50, 2015).

Relating to the work required during the 2013-2015 EBOV pandemic and the difficulties faced by medical staff in the field of the pandemic, more generally, the methods of the present invention accelerate sequencing to obtain results from sample collection. allows sequencing to be performed with fewer probes selected to reduce the time required to obtain Additionally, the kits and systems may be designed for field use to facilitate patient diagnosis without the need to send samples to countries or other parts of the world.

In any of the above methods, any of the sequencing methods described above may be used to sequence the target sequence or fragments thereof. Additionally, sequencing of the target sequence or fragments thereof may be near real-time sequencing. Sequencing of the target sequence or fragments thereof may be performed according to the methods described above (Experimental Procedures: Matranga et al., 2014; and Gire, et al., 2014). Sequencing a target sequence or fragment thereof may involve parallel sequencing of multiple target sequences. Sequencing of the target sequence or fragments thereof may comprise Illumina sequencing.

An analysis of a target sequence or fragment thereof that hybridizes to one or more of the selected probes may be an identification analysis, wherein hybridization of the selected probes to the target sequence or fragments thereof results in Indicates that the target sequence is present.

Currently, primary diagnostic methods are based on patient symptoms. However, various diseases may share the same symptoms, and diagnostics rely heavily on statistics. For example, malaria induces cold-like symptoms: headache, fever, shivering, joint pain, vomiting, hemolytic anemia, jaundice, urinary hemoglobin, retinal damage, and convulsions. These symptoms are also common in sepsis, gastroenteritis, and viral illness. Among the latter, Ebola has symptoms such as fever, sore throat, muscle pain, headache, vomiting, diarrhea, rash, liver and kidney dysfunction, internal and external bleeding.

For example, when a patient appears in a medical unit in tropical Africa, the basic diagnostic concludes that it is malaria. Malaria is statistically the most probable disease in this region of Africa. As a result, patients are treated for malaria, but they may not actually have malaria, and the patients are not treated correctly. Especially when a patient suffers from a rapidly evolving disease, lack of access to correct treatment can be life threatening. When the medical staff realizes that the treatment given to the patient is ineffective, it may be too late before the correct diagnosis is reached and the patient is properly treated.

The method of the present invention provides a solution to such situations. In fact, the number of guide RNAs is dramatically reduced so that the method of the invention can be provided with a single tip selection probe. The probes are divided into multiple groups, each specific to one disease, so that multiple diseases (eg, viral infections) can be diagnosed at the same time. Thanks to the invention, 4 or more diseases, preferably 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more diseases can be diagnosed by one chip at the same time. The disease is preferably a disease that commonly occurs within a population in a given geographic area. Because each group of selected probes is specific to one of the diseases to be diagnosed, a more accurate diagnosis can be made, thus reducing the risk of wrongly treating the patient.

In other cases, diseases such as viral infections may occur without any symptoms, or may cause symptoms that go away before the patient visits medical staff. In such cases, the patient does not seek any medical help, and the diagnosis is difficult due to the absence of symptoms on the day of the visit to the medical staff.

The present invention may also be used with other methods of diagnosing disease, identifying pathogens, and optimizing therapy based on the detection of nucleic acids such as mRNA in raw, unpurified samples.

The method of the present invention also provides a powerful tool for dealing with such situations. Indeed, because a single diagnostic contains multiple groups of selected guide RNAs, each group specific to the most commonly occurring disease within a given geographic population, medical staff A biological sample taken from a patient is simply brought into contact with the chip. Reading the chip reveals the disease the patient has.

In some cases, patients visit medical staff for diagnosis of certain symptoms. The methods of the present invention can not only identify the disease causing these symptoms, but also determine whether the patient is developing other diseases of which he is unaware.

This information may be of paramount importance when looking for outbreak mechanisms. In fact, groups of patients with the same virus show temporal patterns that suggest a link of transmission from subject to subject.

In some embodiments, the CRISPR system or methods of use thereof described herein may be used to predict disease outcome in patients experiencing viral disease. In certain embodiments, viral illnesses may include, but are not necessarily limited to, Lassa fever. Specific factors associated with Lassa fever may include, but are not necessarily limited to, age, degree of kidney damage, and/or central nervous system (CNS) damage.

Screening for microbial genetic perturbations

In certain exemplary embodiments, the CRISPR system disclosed herein may be used to screen for microbial genetic perturbations. Such methods may be useful, for example, for creating microbial pathways and functional networks. Microbial cells may be genetically modified and screened under different experimental conditions. As noted above, the embodiments disclosed herein may sort multiple target molecules in one sample, or one target in one discrete volume in a multiplexed manner. A genetically modified microorganism may be modified to contain a nucleic acid barcode sequence that identifies a particular genetic alteration carried by one particular microbial cell or population of microbial cells. A barcode is a short sequence of nucleotides (eg, DNA, RNA, or a combination thereof) used as an identifier. Nucleic acid barcodes are 4-100 nucleotides in length and are single- or double-stranded. Methods for identifying cells with barcodes are known in the art, so the barcodes can be detected using the guide RNAs of the CRISPR effector systems described herein. Good.Detection of a detectable positive signal indicates the presence of a particular genetic modification in the sample.The methods disclosed herein can be used as a supplement to demonstrate the effect of the genetic modification in the experimental conditions tested. Genetic alterations screened include, but are not limited to, gene knock-ins, gene knock-outs, inversions, translocations, rearrangements, 1 insertions, deletions, substitutions, mutations of one or more nucleotides, or additions of nucleic acids that encode epitopes that have functional consequences such as altering protein stability or detection, etc. Also described herein. Methods may be used in synthetic biology applications to screen the function of specific arrangements of gene regulatory elements and gene expression modules.

In certain exemplary embodiments, these methods may be used to screen for hypomorphs (allelic variants with reduced expression of traits). PCT/US2016/060730 filed November 4, 2016 entitled "Multiplex High-Resolution Detection of Micro-organism Strains, Related Kits, Diagnostic Methods and Screening Assays", the contents of which are incorporated herein by reference. incorporate into

Different experimental conditions may include exposing the microbial cells to different chemical agents, combinations of chemical agents, different concentrations of chemical agents or combinations of chemical agents, different durations of exposure to chemical agents or combinations of chemical agents, different physical parameters, or the like. It may contain both. In certain exemplary embodiments, the chemical agent is an antibiotic or antiviral agent. Different physical parameters that are screened may include different temperatures, atmospheric pressures, different gas concentrations at atmospheric and non-atmospheric pressures, different pH levels, different medium compositions, or combinations thereof.

Screening of environmental samples

The methods disclosed herein may also be used to screen environmental samples for contaminants by detecting the presence of target nucleic acids or polypeptides. For example, in some embodiments, the invention provides methods of detecting microorganisms. The method comprises exposing a CRISPR system described herein to a sample, and combining one or more guide RNAs with one or more microbe-specific target RNAs or one or more microbe-specific target RNAs such that a detectable positive signal is produced. activating the RNA effector protein by binding to one or more species of trigger RNA. A positive signal may be detected, indicating the presence of one or more microorganisms in the sample. In some embodiments, the CRISPR system may be on the substrate surface described herein, and the substrate may be exposed to the sample. In other embodiments, the same and/or different CRISPR systems may be applied to multiple discrete locations on the substrate. In further embodiments, different CRISPR systems may detect different microorganisms at each location. As described in more detail above, the substrate may be a flexible material substrate, such as, but not limited to, a paper substrate, a cloth substrate, or a flexible polymer substrate.

According to the present invention, the substrate may be passively exposed to the sample by temporarily immersing the substrate in the collected fluid, applying the fluid to be tested to the substrate, or contacting the surface to be tested with the substrate. Any suitable method of introducing good sample to the substrate may be used.

As described herein, samples for use in the present invention can be biological or environmental samples such as food samples (fresh fruit or vegetables, meat), beverage samples, paper surfaces, cloth surfaces, It may be a metal surface, a wood surface, a plastic surface, a soil sample, a freshwater sample, a wastewater sample, a saline sample, an air or other gaseous sample, or a combination thereof. For example, household/commercial/industrial surfaces of any material including, but not limited to, metal, wood, plastic, rubber, etc. may be wiped and tested for contaminants. Soil samples may be tested for the presence of pathogenic bacteria or parasites, or other microorganisms, for environmental purposes and/or for human, animal, or plant disease testing purposes. Evaluating water samples, such as freshwater samples, wastewater samples, saline samples, etc., for cleanliness and safety and/or portability, for example, to detect the presence of Cryptosporidium parvum, Giardia lamblia, or other microbial contamination You may In further embodiments, the biological sample includes, but is not limited to tissue samples, saliva, blood, plasma, serum, feces, urine, saliva, mucus, lymph, synovial fluid, cerebrospinal fluid, ascites, pleural effusion, seroma, It may be obtained from sources including pus or swabs of skin or mucosal surfaces. Depending on the particular embodiment, the environmental or biological sample may be a raw sample and/or one or more target molecules may have been purified or amplified from the sample prior to applying the method. Identification of microorganisms may be useful and/or necessary in any number of applications. Thus, the present invention may use any type of sample from any source deemed appropriate by those skilled in the art.

In some embodiments, testing restaurants or other food providers for food contamination with bacteria such as E. coli; food surfaces; testing water for pathogens such as Salmonella, Campylobacter, or E. coli; identifying air contamination with pathogens such as Legionella; determining whether beer has been contaminated or spoiled with pathogens such as pediococcus and lactobacilli contamination of pasty or non-pasty cheeses with bacteria or fungi during manufacture.

Microorganisms according to the invention may be pathogenic microorganisms or microorganisms that spoil food or consumer products. Pathogenic microorganisms may be pathogenic or otherwise undesirable to humans, animals, or plants. For human or animal purposes, the microorganism may be disease-causing or disease-causing. Animal or veterinary uses of the present invention may identify animals infected with microorganisms. For example, the methods and systems of the present invention may identify pets with pathogens including, but not limited to, canine kennel cough, rabies virus, and heartworm. In other embodiments, the methods and systems of the present invention may be used for paternity identification for breeding purposes. Plant microorganisms can cause plant damage or disease, reduce yield, or alter properties such as color, taste, consistency, and odor. For purposes of contaminating food or consumables, microorganisms can adversely affect the taste, odor, color, consistency, or other commercial properties of food or consumables. In certain exemplary embodiments, the microorganism is a bacterial species. The bacteria may be psychrophilic bacteria, E. coli, lactic acid bacteria, or spore-forming bacteria. In certain exemplary embodiments, the bacterium may be any bacterial species that causes disease or illness or otherwise undesirable product or characteristic. A bacterium according to the invention may be pathogenic to humans, animals, or plants.

Sample type

Suitable samples for use in the methods disclosed herein include any conventional biological sample obtained from organisms such as plants, animals, bacteria, or parts thereof. In certain embodiments, biological samples are obtained from animal subjects, such as human subjects. A biological sample is any solid or fluid sample obtained from or excreted or secreted from any living organism. Such organisms include, but are not limited to, unicellular organisms (eg, bacteria, yeast, protozoa, and amoeba, among others), multicellular organisms (eg, plants or animals). Such samples include those from healthy or appearing healthy human subjects or patients under diagnosis or investigation who are affected by a medical condition or disease (e.g., infection with a pathogenic microorganism (e.g., pathogenic bacteria or virus)). sample. For example, a biological sample may be, for example, blood, plasma, serum, urine, feces, saliva, mucus, lymphatic fluid, synovial fluid, bile, ascites, pleural effusion, seroma, saliva, cerebrospinal fluid, aqueous humor or vitreous humor, any body secretions, exudates, exudates (e.g., fluids obtained from an abscess or any other site of infection or inflammation), or joints (e.g., normal joints or rheumatoid arthritis, osteoarthritis, gout, or sepsis) joints affected by disease, such as arthritis), or bodily fluids obtained from swabs of skin or mucosal surfaces.

A sample may also be a sample obtained from any organ or tissue (including biopsy or autopsy samples, such as tumor biopsies) and any cell, tissue, or organ conditioned cell (primary cells or cultured cells) or medium. Exemplary samples include, but are not limited to, cells, cell lysates, blood smears, cytocentrifuge preparations, cell smears, bodily fluids (e.g., blood, plasma, serum, saliva, saliva, urine, bronchopulmonary Cyst lavages, semen, etc.), tissue biopsies (eg, tumor biopsies), fine needle aspirates, and/or tissue sections (eg, frozen tissue sections and/or paraffin-embedded tissue sections). In other examples, the sample contains circulating tumor cells (which can be identified by cell surface markers). In certain instances, the sample is used directly (e.g., fresh or frozen) or, for example, by fixing (e.g., with formalin) and/or embedding in wax (e.g., formalin-fixed paraffin) prior to use. Embedded (FFPE) tissue samples) may be manipulated. Obviously, any method of obtaining tissue from a subject may be used, and the choice of method used will depend on various factors such as the type of tissue, age of the subject, or procedures available to the physician. there is Standard techniques for obtaining such samples are available in the art. For example, Schluger et al., J. Exp. Med. 176:1327-33 (1992); Bigby et al., Am. Rev. Respir. Dis. 133:515-18 (1986); 318:589-93 (1988); and Ognibene et al., Am. Rev. Respir. Dis. 129:929-32 (1984).

In other embodiments, the sample may be an environmental sample, eg, water soil, or a surface such as an industrial or medical surface. In some embodiments, the methods disclosed in U.S. Patent Publication No. 2013/0190196 are used to directly detect nucleic acid signatures (particularly RNA concentrations) from live cell samples with high sensitivity and specificity. may BLAST software may be used to compare the coding sequences from the pathogen of interest with the coding sequences of all other organisms to identify or select sequences specific to each pathogen of interest.

Some embodiments of the present disclosure involve the use of procedures and methods known in the art to successfully fractionate clinical blood samples. For example, Han Wei Hou et al., Microfluidic Devices for Blood Fractionation, Micromachines 2011, 2, 319-343; Ali Asgar S. Bhagat et al., Dean Flow Fractionation (DFF) Isolation of Circulating Tumor Cells (CTCs) from Blood, 15th International Conference on Miniaturized Systems for Chemistry and Life Sciences, October 2-6, 2011, Seattle, WA; and International Patent See procedures described in Publication No. WO2011109762. These disclosures are incorporated herein by reference in their entirety. Blood samples are generally swollen with culture medium to increase the size of the sample for testing purposes. In some aspects of the invention, blood or other biological samples may be used in the methods described herein without the need to expand with culture medium.

Additionally, some embodiments of the present disclosure include the use of procedures and methods known in the art to successfully isolate pathogens from whole blood using spiral microgrooves. These can be found in Han Wei Hou et al., Pathogen Isolation from Whole Blood Using Spiral Microchannel, Case No. 15995JR, Massachusetts Institute of Technology, manuscript in preparation and the disclosure of which is incorporated herein by reference in its entirety.

Due to the increased sensitivity of the embodiments disclosed herein, certain exemplary embodiments employ assays and methods in raw samples, or in which the target molecules to be detected are further fractionated or purified from the sample. It may also be performed on samples without

Exemplary microorganism

Multiple different microorganisms may be detected using the embodiments disclosed herein. The term "microorganism" as used herein includes bacteria, fungi, protozoa, parasites, and viruses.

bacteria

Below is an exemplary list of types of microorganisms that may be detected using the embodiments disclosed herein. In certain exemplary embodiments, said microorganism is a bacterium. Examples of bacteria that can be detected according to the disclosed methods include, but are not limited to, any one or more of the following (or any combination thereof), among others: Acinetobacter baumannii, Actinobacillus, Actinomycetes. , Actinomyces (e.g., Actinomyces Israeli and Actinomyces naeslundi), Aeromonas (e.g., Aeromonas hydrophila, Aeromonas veronii subgenus Sobria (Aeromonas sobria), and Aeromonas caviae), Ana Plasma phagocytophilum, Anaplasma marginale, Alcaligenes xylosoxydans, Acinetobacter baumannii, Actinobacillus actinomycetemcomitans, Bacillus genus (e.g., Bacillus anthracis, Bacillus cereus, Bacillus subtilis, Bacillus thuringiensis , and Bacillus stearothermophilus), Bacteroides (e.g. Bacteroides fragilis), Bartonella (e.g. Bartonella basiformis and Bartonella henselae), Bifidobacterium, Bordetella (e.g. Bordetella pertussis) , Bordetella parapertussis, and Bordetella bronchiseptica), Borrelia (e.g., Borrelia recalentis, and Borrelia burgdorferi), Brucella (e.g., Brucella avoltus, Brucella canis, Brucella melitensis, and Brucella suisse) , Bucorderia (e.g., Bucorderia pseudomallei, and Bucorderia cepacia), Campylobacter (e.g., Campylobacter jejuni, Campylobacter coli, Campylobacter rari, and Campylobacter fetus), Capnocytophaga, Cardiobacterium hominis, Chlamydia trachomatis, Chlamydophila pneumoniae, Chlamydophila sitassi, Citrobacter spp. ), Clostridium (e.g., Clostridium perfringens, Clostridium difficile, Clostridium botulinum, and Clostridium tetani), Eikenella colodens, Enterobacter (e.g., Enterobacter aerogenes, Enterobacter agglomerans, Enterobacter cloaca, and E. coli (including opportunistic E. coli such as enterotoxigenic E. coli, invasive E. coli, pathogenic E. coli, enterohemorrhagic E. coli, enteroaggregative E. coli, and uropathogenic E. coli), Enterococcus genera (e.g., Enterococcus faecalis and Enterococcus phaechium), Ehrlichia (e.g. Ehrlichia chaffeensia, and Ehrlichia canis), Epidermophyton floccosum, Erysipelothus swine, Eubacterium, Francisella tularensis, Fusobacterium nucleatum, Gardnerella vaginalis, Gemera morbilorum , Haemophilus (e.g., Haemophilus influenzae, Haemophilus molluscum, Haemophilus aegyptus, Haemophilus parainfluenzae, Haemophilus haemolyticus, and Haemophilus parahaemolyticus), Helicobacter (e.g., Helicobacter pylori, Helicobacter cinedi, and Helicobacter feneriae), Kingella kingii, Klebsiella (e.g., Klebsiella pneumoniae, Klebsiella granulomatis, and Klebsiella oxytoca), Lactobacillus, Listeria monocytogenes, Leptospira interrogans, Legionella pneumophila, Leptospira interrogans, Peptostreptococcus, Mannheimia haemolytica, Microsporum canis, Moraxella catarrhalis, Morganella, Mobiluncus, Micrococcus, Mycobacterium (e.g. Mycobacterium leprae, Mycobacterium tuberculosis, Mycobacterium para tuberculosis, Mycobacterium intracellulare, Mycobacterium avium, Mycobacterium bovis, and Mycobacterium marinum), Mycoplasma genera (e.g., Mycoplasma pneumoniae, Mycoplasma hominis, and Mycoplasma genitalium) , Nocardia sp. (e.g. Nocardia asteroides, Nocardia syriacigeorgica, and Nocardia brasiliensis), Neisseria sp. fungus), Plesiomonas shigeroides. Prevotella, Porphyromonas, Prevotella melaninogenica, Proteus (e.g. Proteus vulgaris and Proteus mirabilis), Providencia (e.g. Providencia alcalifaciens, Providencia rettgeri, and Providencia stuarti), green Aeruginosa, Propionibacterium acnes, Rhodococcus equi, Rickettsia spp. , Rhodococcus spp., Serratia marcescens, Stenotrophomonas maltophila, Salmonella spp. Serratia marcesans and Serratia licefaciens), Shigella spp. Staphylococcus epidermidis, Staphylococcus haemolyticus, Staphylococcus saprophyticus), Streptococcus spp. Streptococci, Streptomycin-resistant serotype 9V Streptococcus pneumoniae, Erythromycin-resistant serotype 14 Streptococcus pneumoniae, Optkin-resistant serotype 14 Streptococcus pneumoniae, Rifampicin-resistant serotype 18C Streptococcus pneumoniae, Tetracycline-resistant serotype 19F Streptococcus pneumoniae, Penicillin-resistant serum Streptococcus pneumoniae type 19F and trimethoprim-resistant serotype 23F Streptococcus pneumoniae, chloramphenicol-resistant serotype 4 Streptococcus pneumoniae, spectinomycin-resistant serotype 6B Streptococcus pneumoniae, streptomycin-resistant serotype 9V Streptococcus pneumoniae, optkin-resistant serotype 14 Streptococcus pneumoniae, rifampicin-resistant serotype 18C Streptococcus pneumoniae, penicillin-resistant serotype 19F Streptococcus pneumoniae, or trimethoprim-resistant serotype 23F Streptococcus pneumoniae), Streptococcus agalactiae, Streptococcus mutans, Streptococcus pyogenes, Group A Streptococcus pyogenes, Streptococcus pyogenes, Group B Streptococcus, Streptococcus agalactiae, Group C Streptococcus, Streptococcus anginosus, Streptococcus equismilis, Group D Streptococcus, Streptococcus bovis, Group F Streptococcus, and Streptococcus anginosus Group G Streptococcus coccus), Spirium minus, Streptobacillus moniliformi, Treponema spp. Plasma urealyticum, Veillonella, Vibrio (e.g., Vibrio cholerae, Vibrio parahaemolyticus, Vibrio vulnificus, Vibrio parahaemolyticus, Vibrio vulnificus, Vibrio alginolyticus, Vibrio mimicus, Vibrio parahaemolyticus) horisae, Vibrio fluvialis, Vibrio mechnicophili, Vibrio damselae, and Vibrio flunisii), Yersinia (eg, Yersinia enterocolitica, Yersinia enterocolitica, Yersinia pestis, and Yersinia pseudotuberculosis), and Xanthomonas maltophila.

fungus

In certain exemplary embodiments, the microorganism is a fungus or genus Fungi. Examples of fungi that can be detected by the disclosed methods include, but are not limited to, any one or more of the following (or any combination thereof): Aspergillus, Blastomyces, Candidiasis, Coccidiodomycosis, Cryptococcus neoformans, Cryptococcus gattii species, Histoplasma (e.g. Histoplasma capsulatum), Pneumocystis (e.g. Pneumocystis jirovecii), Stachybotrys (e.g. Stachybotrys chartarum), Mucromycosis, Sporothrix, Fungal eye infections Trichophyton, Exserohilum, Cladosporium.

In certain exemplary embodiments, the fungus is yeast. Examples of yeast that can be detected by the disclosed methods include, but are not limited to, any one or more of the following (or any combination thereof): Aspergillus (e.g., Aspergillus fumigatus, Aspergillus flavus, and Aspergillus cravatus), Cryptococcus (e.g. Cryptococcus neoformans, Cryptococcus gattii, Cryptococcus laurentii, and Cryptococcus albidus), Geotrichum, Saccharomyces, Hansenula, Candida ( For example, Candida albicans), Kluyveromyces, Debaryomyces, Pichia, or combinations thereof. In certain exemplary embodiments, the fungi are molds. Examples of molds include, but are not limited to, Blue mold, Cladosporium, Bisochlamys, or combinations thereof.

protozoa

In certain exemplary embodiments, the microorganism is a protozoan. Examples of protozoa that can be detected by the disclosed methods and devices include, but are not limited to, any one or more of Euglenozoa, Heterobocea, Dipromonadida, Amoebozoa, Blastocystis, and Apicomplexa (or any combination thereof). are mentioned. Examples of Euglenozoa include, but are not limited to, Trypanosoma cruzi (Chagas disease), Trypanosoma brucei gambiense, Trypanosoma brucei desiense, Leishmania brasiliensis, Leishmania infantum, Leishmania Mania mexicana, Leishmania major, Leishmania tropica, and Leishmania donovani. Examples of heterorobocea include, but are not limited to, Naegleria fowleri. Examples of Dipromonadida include, but are not limited to, Giardia intestinalis (Giardia lamblia, Giardia duodenalis duodenalis). Examples of amoebozoa include, but are not limited to, Acanthamoeba castellanii, Balamuthia mandrillaris, Entamoeba histolytica, examples of Blastocystis include, but are not limited to, Blastocystis hominis. Examples of Apicomplexa include, but are not limited to, Babesia microti, Cryptosporidium parvum, Cyclospora caietanensis, Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, Plasmodium malariae, and Toxoplasma gondii, Babesia・Microti, Cryptosporidium. Mu parvum, Cyclospora caietanensis, Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, Plasmodium malariae, and Toxoplasma gondii.

Parasite

In certain exemplary embodiments, the microorganism is a parasite. Parasites that can be detected by the disclosed methods include, but are not limited to, any one or more of the genera Onchocerca and Plasmodium (or any combination thereof).

virus

In certain exemplary embodiments, the systems, devices, and methods disclosed herein relate to detecting viruses in samples. Embodiments disclosed herein may be used to detect viral infections (eg, in subjects or plants) or to determine viral strains, including viral strains that differ by single nucleotide polymorphisms. Viruses may be DNA viruses, RNA viruses, or retroviruses. Non-limiting examples of viruses useful in the present invention include, but are not limited to: Ebola virus, Measles virus, SARS virus, Chikungunya virus, Hepatitis virus, Marburg virus, Yellow fever virus, MERS. viruses, dengue virus, lassa virus, influenza virus, rhabdovirus, or HIV rhabdovirus. The hepatitis virus may include hepatitis A virus, hepatitis B virus, or hepatitis C virus. Influenza viruses may include, for example, influenza A or influenza B. HIV may include HIV1 or HIV2. In certain exemplary embodiments, the viral sequences may be: human respiratory syncytial virus, Sudan Ebola virus, Bundibugyo virus, Tai Forest Ebola virus, Reston Ebola virus, Atimota virus, Aedes flavivirus, Aguacatevirus, Akabane virus, Alethinophid reptarenavirus, Allpahuayo mammarenavirus, Amapari mmarenavirus, Andean virus, Apoivirus, Alabang Viruses, Alloavirus, Almwotovirus, Atlantic Salmon Paramyxovirus, Australian Bat Lyssavirus, Avian Bornavirus, Avian Metapneumovirus, Avian Paramyxovirus, Penguin or Falkland Island Virus, BK Polyomavirus, Bagazavirus, Bannavirus, bat hepevirus, bat sapovirus, bear canon manmarenavirus, veyron virus, betacoronavirus, betapapillomavirus 1-6, bahnyavirus, Bokello bat morilyssavirus, Borna disease virus, bourbon virus, bovine hepacivirus Viruses, bovine parainfluenza virus 3, bovine respiratory syncytial virus, brazolan virus, bunyamwella virus, caliciviridae virus. California encephalitis virus, Candir virus, Canine distemper virus, Canine pneumovirus, Cedar virus, Cell fusion factor virus, Whale morbillivirus, Chandipura virus, Chaoyang virus, Chapare mammarenavirus, Chikungunya virus, Colobus monkey papilloma virus Viruses, Colorado tick fever virus, Cowpox virus, Crimean-Congo hemorrhagic fever virus, Culex flavivirus, Cupixi mammarena virus, Dengue virus, Dobrava-Belgredo virus, Donggang virus, Dugbe virus, Dubenhage virus, Eastern equine encephalitis virus, Entebbe bat virus, Enteroviruses AD, European bat Lyssavirus 1-2, Eyach virus, Feline morbillivirus, Feldrans paramyxovirus, Fitzroy River virus, Flavivirus family viruses, flexal manmarenavirus, GB virus C, Gairo virus, gemicircular virus, goose paramyxovirus SF02, great island virus, guanalithmanmarenavirus, hantavirus, hantavirus Z10, heartland virus, Hendra virus, hepatitis A/B/C/E virus, hepatitis delta virus, human bocavirus, human coronavirus, human endogenous retrovirus K, human enteric coronavirus, human genthal-associated circular DNA virus-1, human herpes Viruses 1-8, Human Immunodeficiency Virus 1/2, Human Mastadenovirus A-G, Human Papillomavirus, Human Parainfluenza Viruses 1-4, Human Parechovirus, Human Picovirnavirus, Human Smacovirus, Icomarissa virus, Irheus virus, Influenza A to C, Ippimanmarenavirus, Irkutz virus, J-virus, JC Polyomavirus, Japanese encephalitis virus, Juninmanmarenavirus, KI Polyomavirus, Cadipirovirus, Kamichi Kamiti River virus, Kedou Gou virus, Kujang virus, Cocobella virus, Kyasanul forest disease virus, Lagos bat virus, Langat virus, Lassamanmarenavirus, Latinomanmarenavirus, Leopards Hill virus, Liaoning virus ning) virus, Ljungan virus, Lloviu virus, Jumping disease virus, Lujomanmarenavirus, Lunamanmarenavirus, Lunk virus, Lymphocytic Choriomeningitis Mammarenavirus, Lyssavirus Ozer Noe, MSSI2\. 225 virus, Machupo Mammarena virus, Mamastrovirus 1, Manzanilla virus, Mapuera virus, Marburg virus, Mayoro virus, Measles virus, Menanglu virus, Mercadeovirus, Merkel cell polyoma virus, Middle East respiratory syndrome Coronavirus, Mobara Mammarena Virus, Modoc Virus, Moijang Virus, Mocorrovirus, Monkeypox Virus, Montana myotis leukoencephalitis Virus, Mopei Alassa Virus Reassortant 29, Mopeia Mammarena Virus, Morogoro Viruses, Mosman virus, Mumps virus, Murine pneumonia virus, Murray Valley encephalitis virus, Nariva virus, Newcastle disease virus, Nipah virus, Norwalk virus, Norwegian rat hepacivirus, Taya virus, Onyong Nyong virus, Oliverosman malenavirus, Omsk hemorrhage Fever Virus, Oropouche Virus, Parainfluenza Virus 5, Paranamammarenavirus, Parramatta River Virus, Small Ruminant Pesticide Virus, Pichande Mammarenavirus, Picornaviridae Virus, Piritarmanmarenavirus, Piscihepe ) Virus A, porcine parainfluenza virus 1, porcine bra virus, Poissan virus, primate T lymphotropic virus 1-2, primate erythroparvovirus 1, puntatro virus, pumala virus, cambin virus, rabies virus , razudan virus, reptilian bornavirus 1, rhinovirus A-B, Rift Valley fever virus, rinderpest virus, riobravo virus, rodent torctenovirus, rodent hepacivirus, Ross River virus, rotavirus A-I, Royal farm virus, Rubella virus, Sabia Mammarena virus, Salem virus, Sandfly fever Napoli virus, Sandfly fever Sicilian virus, Sapporo virus, Sashperi virus, Seal anellovirus, Semliki forest virus, Sendai virus, Seoul virus , Sepik virus, severe acute respiratory syndrome-associated coronavirus, hyperthermia with thrombocytopenic syndrome virus, Shamonda virus, simon bat virus, shuni virus, simbu virus, simian torctenovirus, simian virus 40-41, shin nomburu virus , Sindbis virus, small anellovirus, Sosuga virus, Spanish goat encephalitis virus, Spondwenyi virus, St. Louis encephalitis virus, Sunshine virus, TTV minivirus, Takaribemanmarena virus, Taila virus, Taman bat virus, Tamiami mammarena virus, Tembus virus, Thogoto virus, Tottapalayan virus, Tick-borne encephalitis virus, Thioman virus, Togaviridae virus, Torctenocanis virus, Torcteno canis virus, Doroucouli Virus, Torquetenofelis virus, Torquetenodivirus, Torquetenosus virus, Torquetenotamarin virus, Torquetenovirus, Torquetenoasika virus, Tsuhoko virus, Tsura virus, Tupia paramyxovirus, Ustu virus, Wukniemi virus, Vaccinia Viruses, smallpox virus, Venezuelan equine encephalitis virus, vesicular stomatitis Indiana virus, WU polyomavirus, Wesselsbron virus, West Caucasian bat virus, West Nile virus, Western equine encephalitis virus, Whitewater arroyoman marena virus, yellow Fever virus, Yokose virus, Yagbogdanobac virus, Zaire Ebola virus, Zika virus, or Zygosaccharomyces Bailivirus Z virus sequences. Examples of RNA viruses that can be detected include any one or more of the following (or any combination thereof): Coronaviridae viruses, Picornaviridae viruses, Caliciviridae viruses, Flaviviridae viruses, Togaviridae viruses. A virus, Bornaviridae, Filoviridae, Paramyxoviridae, Pneumovirinae, Rhabdoviridae, Arenaviridae, Bunyaviridae, Orthomyxoviridae, or Deltavirus. In certain exemplary embodiments, the virus is coronavirus, SARS, poliovirus, rhinovirus, hepatitis A, Norwalk virus, yellow fever virus, West Nile virus, hepatitis C virus, dengue virus, Zika virus, Rubella virus, Ross River virus, Sindbis virus, Chikungunya virus, Borna virus, Ebola virus, Marburg virus, Measles virus, Mumps virus, Nipah virus, Hendra virus, Newcastle disease virus, Human respiratory syncytial virus, Rabies virus, Lassa virus, hantavirus, Crimean-Congo hemorrhagic fever virus, influenza, or hepatitis D virus.

In certain exemplary embodiments, the virus may be a plant virus selected from the group comprising: Tobacco Mosaic Virus (TMV), Tomato Spotted Wilt Virus (TSWV), Cucumber Mosaic Virus (CMV). , Potato Virus Y (PVY), Retrovirus Cauliflower Mosaic Virus (CaMV), Prunus Prunus Root Virus (PPV), Brome Mosaic Virus (BMV), Potato Virus X (PVX), Citrus Tristeza Virus (CTV), Barley Yellow Dilter virus (BYDV), potato leaf curl virus (PLRV), tomato dwarf virus (TBSV), rice dwarf virus (RTSV), rice yellow spot virus (RYMV), rice white leaf disease virus (RHBV), maize rayadofinovirus (MRFV), corn dwarf mosaic virus (MDMV), sugar cane mosaic virus (SCMV), sweet potato spot mosaic virus (SPFMV), sweet potato sunken vein closterovirus (SPSVV), grape fan leaf virus (GFLV) , Grape virus A (GVA), Grape virus B (GVB), Grape fleck virus (GFkV), Grape leaf curl-associated virus-1, -2, and -3, (GLRaV-1, -2, and -3), Arabis mosaic virus (ArMV), or grape stem pitting-associated virus (RSPaV). In one preferred aspect, the target RNA molecule is part of said pathogen or is transcribed from a DNA molecule of said pathogen. For example, the target sequence may be contained in the genome of an RNA virus. More preferably, when said pathogen infects or is infecting said plant, the CRISPR effector protein hydrolyzes a target RNA molecule of said plant pathogen. Thus, whether the CRISPR system (or the parts necessary for its completion) is applied as a treatment after an infection has occurred or as a prophylaxis before an infection has occurred, the CRISPR system cleaves the target RNA molecule from the plant pathogen. preferably be able to

In certain exemplary embodiments, the virus may be a retrovirus. Examples of retroviruses that can be detected using the embodiments disclosed herein include alpharetroviruses, betaretroviruses, gammaretroviruses, deltaretroviruses, epsilon retroviruses, lentiviruses, spumavirus viruses, or one or more of the Metaviridae, Pseudoviridae, and Retroviridae (including HIV), Hepadnaviridae (including Hepatitis B virus), and Calimoviridae (including Cauliflower Mosaic Virus) viruses, or Any combination thereof is included.

In certain exemplary embodiments, the virus is a DNA virus. Examples of DNA viruses that can be detected using the embodiments disclosed herein include Myoviridae, Podoviridae, Siphoviridae, Alloherpesviridae, Herpesviridae (human herpesvirus, and varicella-zoster virus). viruses), Marocoviridae, Liposurixviridae, Rudiviridae, Adenoviridae, Amplaviruses, Ascoviridae, Asphaviridae (including African swine fever virus), Baculoviridae, Cicaudaviridae Cicaudaviridae, Clavaviridae, Corticoviridae, Fuseroviridae, Globroviridae, Guttaviridae, Humanrosaviridae, Iridoviridae, Maseilleviridae, Mimiviruses family, Nudiviridae, Nimaviridae, Pandoraviridae, Papillomaviridae, Phycodnaviridae, Plasaviridae, Polydnaviridae, Polyomaviridae (including Simianvirus 40, JC virus, BK virus), Poxviridae (including cowpox and smallpox), Sphaerolipoviridae, Tektiviridae, Turriviridae, Dinodnavirus, Salterprovirus, Lysidovirus ( Rhizidovirus) (or any combination thereof). In some embodiments, methods of diagnosing a species-specific bacterial infection in a subject suspected of having a bacterial infection are described. The method comprises obtaining from a subject a sample containing bacterial ribosomal ribonucleic acid; contacting the sample with one or more of the above probes to allow hybridization of the probes to bacterial ribosomal ribonucleic acid sequences present in the sample. detecting, wherein the subject is Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus Staphylococcus, Acinetobacter baumannii, Candida albicans, Enterobacter cloacae, Enterococcus faecalis, Enterococcus faecium, Infection with Proteus mirabilis, Staphylococcus agalactiae, Staphylococcus maltophila, or a combination thereof.

In certain exemplary embodiments, the virus is a virus shown in Table 8 below, or a virus of the indicated genus/family.

In certain aspects, the virus is a virus shown in the table below.

In certain aspects, the virus is a virus shown in Table 9 below.

In certain aspects, the virus is a drug-resistant virus. By way of example, but not limitation, the virus may be a ribavirin resistant virus. Ribavirin is a highly effective antiviral that attacks multiple RNA viruses. Below are some important viruses that have evolved ribavirin resistance. Foot-and-mouth disease virus: doi:10.1128/JVI.03594-13. Poliovirus: www.pnas.org/content/100/12/7289.full.pdf. Hepatitis C virus: jvi.asm.org/content/79/4/2346.full. Several other resistant RNA viruses, such as hepatitis and HIV viruses, have evolved resistance to existing antiviral drugs. Hepatitis B virus (lamivudine, tenofovir, entecavir): doi:10.1002/hep.22900. Hepatitis C virus (telaprevir, BILN2061, ITMN-191, SCH6, boceprevir, AG-021541, ACH-806): doi:10.1002/hep.22549. HIV has many drug resistance mutations. See HIVdb.stanford.edu for more information. In addition to drug resistance, there are multiple clinically relevant mutations that can be targeted with the CRISPR system according to the invention described herein. For example, resistance versus acute infection of lymphocytic choriomeningitis virus (LCMV): doi:10.1073/pnas.1019304108; or increased infectivity of Ebola: http://doi.org/10.1016/j.cell.2016.10 .014 and http://doi.org/10.1016/j.cell.2016.10.013.
Malaria detection and surveillance

Malaria is a mosquito-borne disease caused by the Plasmodium parasite. These parasites are spread among people through the bite of an infected female Anopheles mosquito. Five Plasmodium genera cause human malaria: Plasmodium falcipalum, Plasmodium vivax, Plasmodium ovale, Plasmodium malariae, and Plasmodium nouresi. According to the World Health Organization (WHO), Plasmodium falciparum and Plasmodium vivax pose the greatest threat among these. P. Falcipalum is the most prevalent malaria parasite on the African continent and is responsible for most of the malaria-related deaths on the planet. P. Vivax is the predominant malarial parasite in most countries outside Sub-Saharan Africa.

In 2015, 91 countries and territories had malaria transmission. According to the latest WHO estimates, there were 212,000,000 malaria cases in 2015 and 429,000 deaths. In areas of high malaria transmission, children under the age of 5 years were particularly vulnerable to infection, illness and death, with more than two-thirds (70%) of all malaria deaths occurring in this age group. Between 2010 and 2015, malaria deaths in children under five years of age decreased by 29% worldwide. However, malaria remains the leading cause of death in children under the age of five, killing one child every two minutes.

As described by WHO, malaria is an acute febrile illness. In non-immune individuals, symptoms appear 7 days or more after being bitten by an infectious mosquito. The primary symptoms, fever, headache, and chills, may be moderate in severity, making it difficult to recognize malaria, but if not treated within 24 hours, P. Falcipalum malaria can progress to severe disease and even death.

Children with severe malaria often develop one or more of the following symptoms: severe anemia, dyspnea associated with metabolic acidosis, or cerebral malaria. Adults often have multiple organ complications. In malaria-endemic areas, people may develop partial immunity, causing asymptomatic infection.

The development of rapid and efficient diagnostic tests has great public health implications. Indeed, early diagnosis and treatment of malaria not only reduces disease but also prevents mortality, but also contributes to reducing malaria transmission. According to WHO recommendations, all suspected cases of malaria should be confirmed using parasite-based diagnostic tests, especially rapid diagnostic tests, before initiating treatment (published April 2015). WHO Malaria Treatment Guidelines 3rd Edition”).

Resistance to antimalarial therapy is an important health problem that significantly reduces therapeutic strategies. In fact, as reported on the WHO website, P. Faltipalm's resistance to previous generation drugs (eg, chloroquine and sulfadoxine/pyrimethamine (SP)) became widespread in the 1950s and 1960s, undermining malaria control efforts and reversing progress on child survival. Therefore, WHO recommends constant monitoring of antimalarial drug resistance. Indeed, accurate diagnosis may avoid inadequate treatment and extended limits of antimalarial drug resistance.

In the context of the WHO Global Technical Policy on Malaria 2016-2030 (adopted by the World Health Assembly in May 2015), a technical framework is provided for all malaria endemic countries. It is intended to guide and support local and national programs to work together towards the control and eradication of malaria. The measure is ambitious, but achievable global goals have been set:
* To reduce malaria incidence by at least 90% by 2030.
* To reduce malaria mortality by at least 90% by 2030.
* End malaria in at least 35 countries by 2030.
* To prevent malaria resurgence in all malaria-free countries.

The initiative is the result of two years of extensive consultations and involves the participation of more than 400 technical experts from 70 Member States. This strategy is based on three main axes:
* Ensuring universal access to malaria prevention, diagnosis and treatment;
* Accelerating efforts towards eradication and achieving malaria-free status; and * Converting malaria surveillance into core interventions.

Treatments for Plasmodium include arylaminoalcohols such as quinine or quinine derivatives (e.g. chloroquine, amodiaquine, mefloquine, piperaquine, lumefantrine, primaquine); lipophilic hydroxynaphthoquinone analogues (e.g. atovaquone); antifolate drugs (e.g. For example, the sulfa drugs sulfadoxine, dapthone, and pyrimethamine); proguanil; atovaquone/proguanil combinations; artemisinin drugs), and combinations thereof.

Target sequences used diagnostically for the presence of mosquito-borne pathogens include those of Plasmodium, particularly Plasmodium spp. Includes sequences that are diagnostic for their presence, including those derived from the genome.

Targets used diagnostically to monitor drug resistance of treatments against Plasmodium, particularly Plasmodium genera that affect humans (e.g., Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, Plasmodium malariae, and Plasmodium nouresi) arrangement.

Additionally, target sequences include sequences that include target molecules/nucleic acid molecules that encode proteins involved in important biological processes of Plasmodium parasites. Such proteins include, inter alia, transport proteins (e.g. proteins from the drug/metabolite transport family, ATP-binding cassette (ABC) proteins involved in substrate translocation (e.g. ABC transporter C subfamily or Na ⁺ /H ⁺ exchanger, membrane glutathione S-transferase)); proteins involved in the folate pathway (eg dihydropteroate synthase, dihydrofolate reductase activity or dihydrofolate reductase-thymidylate synthase); and mitochondria Proteins involved in the transfer of protons across the inner membrane, particularly the cytochrome b complex. Additional targets may also include one or more genes encoding heme polymerases.

Furthermore, target sequences include target molecules/nucleic acid molecules that encode proteins involved in important biological processes. Such proteins are P. faltipalm chloroquine resistance transporter (pfcrt), P. faltipalm multidrug resistance transporter 1 (pfmdr1), P. faltipalm multidrug resistance-associated protein gene (Pfmrp), P. faltipalm Na ⁺ /H ⁺ exchanger gene (pfnhe), P. The gene encoding the export protein 1, P. faltipalm. faltipalm Ca2 ⁺ transport ATPase 6 (pfatp6); faltipalm didihydropteroin synthase (pfdhps), dihydrofolate reductase activity (pfdhpr) and dihydrofolate reductase-thymidylate synthase (pfdhfr) gene, cytochrome b gene, gtp cyclohydrolase, Kelch13 (K13) gene, and other Plasmodium functional heterologous genes.

Many mutations, especially single point mutations, have been identified in proteins that are current therapeutic targets and are associated with specific resistance phenotypes. Thus, the present invention allows detection of various resistance phenotypes of mosquito-borne parasites such as Plasmodium.

The invention makes it possible to detect one or more mutations, in particular one or more single nucleotide polymorphisms, in a target nucleic acid/molecule. Accordingly, any one or combination of the following mutations may be used as drug resistance markers and detected by the present invention.

P. Single point mutations in faltipalm K13 are at positions 252, 441, 446, 449, 458, 493, 539, 543, 553, 561, 568, 574, 578, 580, 675, 476, 469, 481, 522, 537, Single point mutations at 538, 579, 584 and 719, especially mutations E252Q, P441L, F446I, G449A, N458Y, Y493H, R539T, I543T, P553L, R561H, V568G, P574L, A578S, C580Y, A675V, M476I; C469Y; N537I; N537D; G538V; M579I; D584V; These mutations are commonly associated with the artemisinin drug resistance phenotype (Artemisinin and artemisinin-based combination therapy resistance, April 2016 WHO/HTM/GMP/2016.5).

P. In faltipalm dihydrofolate reductase (DHFR) (PfDHFR-TS, PFD0830w), the key polymorphisms are mutations at positions 108, 51, 59, and 164, particularly 108D, 164L, 51I, which regulate resistance to pyrimethamine. and 59R. Other polymorphisms also include 437G, 581G, 540E, 436A, and 613S, which have been associated with resistance to sulfadoxine. Further observed mutations include Ser108Asn, Asn51Ile, Cys59Arg, Ile164Leu, Cys50Arg, Ile164Leu, Asn188Lys, Ser189Arg and Val213Ala, Ser108Thr and Ala16Val. The mutations Ser108Asn, Asn51Ile, Cys59Arg, Ile164Leu, Cys50Arg, Ile164Leu are particularly associated with resistance to pyrimethamine-based therapy and/or chloroguanine-dapthone combination therapy. Cycloguanyl resistance appears to be associated with the double mutations Ser108Thr and Ala16Val. Amplification of dhfr may also be highly associated with therapeutic resistance, particularly pyrimethamine resistance.

P. Faltipalm didihydropteroinase (DHPS) (PfDHPS, PF08_0095), important polymorphisms include mutations Ser436Ala/Phe, Ala437Gly, Lys540Glu, Ala581Gly, and Ala613Thr/Ser at positions 436, 437, 581 and 613. Polymorphisms at positions 581 and/or 613 have been associated with sulfadoxine-pyrimethamine system therapy.

P. In the faltipalm chloroquine resistance transporter (PfCRT), a polymorphism at position 76, specifically the mutation Lys76Thr, is associated with resistance to chloroquine. Additionally, polymorphisms include Cys72Ser, Met74Ile, Asn75Glu, Ala220Ser, Gln271Glu, Asn326Ser, Ile356Thr, and Arg371Ile, which can be associated with chloroquine resistance. PfCRT is also phosphorylated at residues S33, S411 and T416, which may modulate transport activity or protein specificity.

P. In the faltipalm multidrug resistance transporter 1 (PfMDR1) (PFE1150w), polymorphisms at positions 86, 184, 1034, 1042, particularly Asn86Tyr, Tyr184-Phe, Ser1034Cys, Asn1042Asp, and Asp1246Tyr, have been identified and lumefan It has been reported to affect sensitivity to thrin, artemisinin, quinine, mefloquine, halofantrine, and chloroquine. Amplification of PfMDR1 has also been associated with reduced sensitivity to lumefantrin, artemisinin, quinine, mefloquine, and halofantrine, and deamplification of PfMDR1 increases chloroquine resistance. Amplification of pfmdr1 may also be detected. The phosphorylation status of PfMDR1 is also highly relevant.

P. In the faltipalm multidrug resistance-associated protein (PfMRP) (genetic reference PFA0590w), polymorphisms at positions 191 and/or 437 (eg, Y191H and A437S) have been identified and associated with a chloroquine resistance phenotype.

P. In the faltipalm NA ⁺ /H ⁺ exchanger (PfNHE) (ref PF13_0019), increased repeats of DNNND at microsatellite ms4670 may be a marker for quinine resistance.

Mutations that alter the ubiquinol binding site of the cytochrome b protein encoding the cytochrome be gene (cytb, mal_mito_3) have been associated with atovaquone resistance. Mutations at positions 26, 268, 276, 133 and 280, particularly Tyr26Asn, Tyr268Ser, M1331 and G280D, may be associated with atovaquone resistance.

For example, P. In Vivax, mutations in the Pf MDR1 homologue, PvMDR1, have been associated with chloroquine resistance, particularly polymorphisms at position 976, eg mutation Y976F.

The above mutations are defined in terms of protein sequence. However, one skilled in the art can determine corresponding mutations, including SNPs, and identify them as nucleic acid target sequences.

Other identified drug resistance markers are known in the art, for example, as described in: “Susceptibility of Plasmodium falciparum to antimalarial drugs”. (1996-2004)"; WHO; Artemisinin and artemisinin-based combination therapy resistance (April 2016 WHO/HTM/GMP/2016.5); "Drug-resistant malaria: molecular mechanisms and implications for FEBS Lett. 2011 Jun 6;585(11):1551-62. doi:10.1016/j.febslet.2011.04.042. Epub 2011 Apr 23. Review. PubMed PMID: 21530510. The entire contents of these are incorporated herein by reference.

Gene products of all genes described herein may be used as targets for polypeptides that can be detected by the present invention. Correspondingly, it is envisioned that such polypeptides may be used for genus identification, classification, and/or detection of drug resistance.

In certain exemplary embodiments, the systems, devices, and methods disclosed herein detect one or more mosquito-borne parasites in a sample, e.g., a biological sample obtained from a subject. Regarding. In certain exemplary embodiments, the parasite may be selected from the following species: Plasmodium falcipalum, Plasmodium vivax, Plasmodium ovale, Plasmodium malariae, or Plasmodium nouresi. Thus, the methods disclosed herein are useful to rapidly identify the parasite species and parasite morphology (e.g., various stages of infection and parasite life cycle (e.g., exoerythrocyte)) necessary to rapidly identify the parasite species. stage, erythroid stage, sporulation stage) and parasite morphology includes daughter parasites, sporozoites, meristematic, gametocytes), monitor specific phenotypes (e.g. detection of pathogen drug resistance, disease and/or epidemic monitoring, and treatment (drug) screening, in other ways (or combinations thereof), and in the case of malaria, after being bitten and infected. A long period of time may elapse, in other words, there is a long incubation period during which the patient does not show symptoms. It may be observed prior to recurrence, and such a delay may easily lead to misdiagnosis, thus compromising treatment efficacy.

The rapid and sensitive diagnostic capabilities of the embodiments disclosed herein, namely the detection of parasite types by single nucleotide differences and the ability to deploy as a POC device, make the embodiments disclosed herein It may be used to guide treatment regimens (eg, selection of an appropriate course of treatment). The embodiments disclosed herein may also be used to screen environmental samples (such as mosquito populations) for the presence and classification of parasites. Embodiments may also be modified to detect mosquito-borne parasites and other mosquito-borne pathogens simultaneously. In some cases, malaria and other mosquito-borne pathogens have similar symptoms in their early stages. Therefore, the ability to quickly distinguish between types of infection may guide important therapeutic decisions. Other mosquito-borne pathogens that can be detected with malaria are Dengue virus, West Nile virus, Chikungunya virus, Yellow Fever virus, Filaria virus, Japanese Encephalitis virus, St. Louis Encephalitis virus, Western Equine Encephalitis virus, Eastern Equine Encephalitis virus, Venezuelan Equine Encephalitis. viruses, La Crosse encephalitis virus, and Zika virus.

In certain exemplary embodiments, the devices, systems, and methods disclosed herein may be used to distinguish between multiple mosquito-borne parasite species in a sample. In certain exemplary embodiments, identification may be based on ribosomal RNA sequences that include the 18S, 16S, 23S, and 5S subunits. In certain exemplary embodiments, identification may be based on gene sequences present in multiple copies of the genome (eg, mitochondrial genes such as CYTB). In certain exemplary embodiments, identification may be based on the sequence of genes that are highly expressed and/or conserved, such as GAPDH, histone H2B, enolase, or LDH. Methods for identifying suitable rRNA sequences are disclosed in US Patent Application Publication No. 2017/0029872. In certain exemplary embodiments, the set of guide RNAs may be designed to distinguish each species by species or strain specific variable regions. Guide RNAs may also be designed against target RNA genes that distinguish microorganisms by genus, family, order, class, phylum, kingdom, or combinations thereof. In certain exemplary embodiments where amplification is used, the set of amplification primers is designed to flanking constant regions of the ribosomal RNA sequence, and the guide RNA may be designed to distinguish between species by internal variable regions. good. In certain exemplary embodiments, the primers and guide RNA may each be designed against the conserved variable region of the 16S subunit. Other genes or genomic regions that vary uniquely across species or subsets of species (eg, RecA gene family, RNA polymerase β subunit) may be used. Other suitable phylogenetic markers and methods of identifying them are described, for example, in Wu et al. arXiv:1307.8690 [q-bio.GN].

In certain exemplary embodiments, species identification may be based on genes that are present in multiple copies of the genome, such as mitochondrial genes such as CYTB. In certain exemplary embodiments, species identification may be based on highly expressed and/or conserved genes (eg, GAPDH, histone H2B, enolase, or LDH).

In certain exemplary embodiments, the method or diagnostic is designed to screen mosquito-borne parasites across multiple phylogenetic and/or phenotypic quantities simultaneously. For example, the method or diagnosis may involve using multiple CRISPR systems with different guide RNAs. The first set of guide RNAs may, for example, distinguish between Plasmodium falciparum and Plasmodium vivax. These general classes may be further subdivided. For example, guide RNAs may be designed and used in methods or diagnostics to distinguish drug-resistant strains generally or with respect to specific drugs or drug combinations. A second set of guide RNAs may be designed to differentiate microorganisms by species. Thus, a matrix identifying all mosquito-borne parasite species or subspecies may be generated and further divided by drug resistance. The above is for illustrative purposes only. Other means of classifying other types of mosquito-borne parasites are also envisioned and follow the general structure above.

In certain exemplary embodiments, the devices, systems, and methods disclosed herein may be used to screen for mosquito-borne parasitic genes of interest, such as, for example, drug resistance genes. Guide RNAs may be designed to distinguish known genes of interest. Accordingly, samples, including clinical samples, may be screened using embodiments that detect one or more such genes disclosed herein. The ability to screen for drug resistance on POC is of great advantage in selecting an appropriate treatment regimen. In certain exemplary embodiments, the drug resistance gene is a protein-encoding gene. Such proteins include, inter alia, transport proteins (e.g. proteins from the drug/metabolite transport family, ATP-binding cassette (ABC) proteins involved in substrate translocation (e.g. ABC transporter C subfamily or Na ⁺ /H ⁺ exchanger)); proteins involved in the folate pathway (e.g., dihydropteroate, dihydrofolate reductase activity or dihydrofolate reductase-thymidylate); and proton transfer across the inner mitochondrial membrane. Proteins involved in metastasis, especially the cytochrome b complex. Additional targets may also include one or more genes encoding heme polymerases. In certain exemplary embodiments, the drug resistance gene is P. faltipalm chloroquine resistance transporter (pfcrt), P. faltipalm multidrug resistance transporter 1 (pfmdr1), P. faltipalm multidrug resistance-associated protein gene (Pfmrp), P. faltipalm Na ⁺ /H ⁺ exchanger gene (pfnhe), P. faltipalm Ca2 ⁺ transport ATPase 6 (pfatp6), P. faltipalm didihydropteroin synthase (pfdhps), dihydrofolate reductase activity (pfdhpr) and dihydrofolate reductase-thymidylate synthase (pfdhfr) gene, cytochrome b gene, gtp cyclohydrolase, Kelch13 (K13) gene, and other Plasmodium functional heterologous genes. Other identified drug resistance markers are known in the art and are described, for example, in “Susceptibility of Plasmodium falciparum to antimalarial drugs” (1996-2004). WHO; Artemisinin and artemisinin-based combination therapy resistance (April 2016 WHO/HTM/GMP/2016.5); “Drug-resistant malaria: molecular mechanisms and implications for public health”; 2011 Jun 6;585(11):1551-62. doi:10.1016/j.febslet.2011.04.042.Epub 2011 Apr 23. Review. PubMed PMID: 21530510. its entire contents are incorporated herein by reference.

In some embodiments, the CRISPR system, detection system or method using the same described herein may be used to determine the occurrence of a mosquito-borne parasite outbreak. The method may comprise detecting one or more target sequences from multiple samples from one or more subjects. Wherein said target sequence is a sequence derived from a mosquito-borne parasite that spreads or causes an outbreak. Such methods may further comprise determining mechanisms involved in transmission of mosquito-borne parasite patterns, or disease outbreaks caused by mosquito-borne parasites. Said sample may be derived from one or more humans and/or may be derived from one or more mosquito species.

Pathogen transmission patterns include continued new infections or other transmissions (e.g., via mosquitoes) from natural sources of mosquito-borne parasites, followed by single infections or both from natural sources. It may be mixed. In one aspect, said target sequence is preferably a sequence within the mosquito-borne parasite genome or a fragment thereof. In one aspect, the pattern of mosquito-borne parasite transmission is the initial pattern of mosquito-borne parasite transmission, ie, the beginning of a mosquito-borne parasite epidemic. Determining patterns of mosquito-borne parasite transmission at the onset of an outbreak increases the likelihood of stopping the outbreak in the earliest possible time, thereby reducing the potential for local and international transmission.

Determining the pattern of mosquito-borne parasite transmission may comprise determining mosquito-borne parasite sequences by the methods described herein. Determining pathogen transmission patterns detects intra-host diversity of shared mosquito-borne parasite sequences in subjects and determines whether shared intra-host diversity exhibits a temporal pattern. It may further include Patterns of intra- and inter-host variability provide important insights into transmission and epidemiology (Gire, et al., 2014).

In addition to other sample types disclosed herein, the sample may be derived from one or more mosquito species, eg, the sample may comprise mosquito saliva.

Biomarker detection

In certain exemplary embodiments, the systems, devices, and methods disclosed herein may be used to detect biomarkers. For example, the systems, devices, and methods disclosed herein may be used for SNP detection and/or genotyping. The systems, devices, and methods disclosed herein may also be used to detect any disease state or disorder characterized by aberrant gene expression. Aberrant gene expression includes abnormalities in the expressed gene, the location of expression, and the amount of expression. Multiple transcript or protein markers associated with cardiovascular, immune disorders, and cancer, among other diseases, may be detected. In certain exemplary embodiments, embodiments disclosed herein may be used for cell-free DNA detection of diseases involving lysis such as liver fibrosis and restrictive/obstructive pulmonary disease. In certain exemplary embodiments, embodiments may be used for faster and more portable detection for prenatal testing of circulating cell-free DNA. Embodiments disclosed herein relate to cardiovascular health, lipid/metabolic signatures, ethnicity identification, paternity matching, human identification (e.g., suspects matched to crime database SNP signatures), among others. It may also be used to screen a panel of different SNPs. Embodiments disclosed herein may also be used for the detection of mutated cell-free DNA released in association with cancerous tumors. Embodiments disclosed herein may also be used to detect meat quality, for example, by quickly detecting different animal sources in a given meat product. Embodiments disclosed herein may also be used to detect genetically modified organisms (GMOs) or DNA-associated gene editing. As described elsewhere herein, closely related genes/alleles or biomarkers (e.g., with only one nucleotide difference in a given target sequence) introduce synthetic mismatches into gRNAs can be distinguished by

In one aspect, the invention relates to methods of detecting target nucleic acids in a sample. The method includes
distributing a sample or set of samples into one or more discrete volumes containing a CRISPR system according to the invention described herein;
incubating said sample or said set of samples under conditions sufficient to allow one or more guide RNAs to bind to one or more target molecules;
activating a CRISPR effector protein by binding of said one or more guide RNAs to one or more target molecules, wherein activation of the CRISPR effector protein produces a detectable positive signal; the RNA-based masking construct is modified); and detecting a detectable positive signal, wherein detection of the detectable positive signal indicates the presence of one or more target molecules in the sample. include.

Type of biomarker sample

The sensitivity of the assays described herein is well suited for detection of target nucleic acids in a variety of biological sample types, including sample types in which the target nucleic acid is diluted or limited in sample material. . Biomarker screening may be performed on multiple sample types. Sample types include, but are not limited to, saliva, urine, blood, feces, saliva, and cerebrospinal fluid. Also, the embodiments disclosed herein may be used to detect up- and/or down-regulation of genes. For example, the sample may be serially diluted so that only overexpressed genes are above the detection limit threshold of the assay.

In certain aspects, the invention provides obtaining a sample of bodily fluid (eg, urine, plasma, serum, saliva, cerebrospinal fluid) and extracting DNA. The mutated nucleotide sequence to be detected may be a fraction of a larger molecule, or may exist as an individual molecule from the beginning.

In a particular aspect, the DNA is isolated from plasma/serum of cancer patients. A second sample may be isolated from non-neoplastic tissue (eg, lymphocytes) from the same patient for comparison with a DNA sample isolated from neoplastic tissue (control). Non-neoplastic tissue may be of the same type as neoplastic tissue or may be derived from a different organ source. In certain embodiments, blood samples are taken and plasma is immediately separated from blood cells by centrifugation. Serum may be filtered and stored frozen until DNA is extracted.

In certain exemplary embodiments, target nucleic acids are detected directly from raw or unprocessed samples (eg, blood, serum, saliva, cerebrospinal fluid, saliva, or urine). In certain exemplary embodiments, the target nucleic acid is cell-free DNA.

circulating tumor cells

In one aspect, circulating cells (eg, circulating tumor cells (CTCs)) may be assayed with the present invention. Isolation of circulating tumor cells (CTCs) for use in any of the methods described herein may be performed. An exemplary technique to achieve specific and sensitive detection and capture of circulating cells that may be used in the present invention is described in (Mostert B, et al., Circulating tumor cells (CTCs): detection methods and their clinical relevance in breast cancer. Cancer Treat Rev. 2009;35:463-474; and Talasaz AH, et al., Isolating highly enriched populations of circulating epithelial cells. and other rare cells from blood using a magnetic sweeper device. Proc Natl Acad Sci U S A. 2009; 106 :3970-3975). As few as one CTC can be found in the background of 105-106 peripheral blood mononuclear cells (Ross A A, et al., Detection and viability of tumor cells in peripheral blood stem cell collections from breast cancer patients using Tumor cell detection and feasibility in collecting peripheral blood stem cells from breast cancer patients using immunocytochemical and clonogenic assay techniques. Blood. 1993, 82:2605-2610). The CellSearch® platform uses antibody-coated immunomagnetic beads against epithelial cell adhesion molecule (EpCAM) to enrich for EPCAM-expressing epithelial cells and immunostains for the presence of cytokeratin staining and the leukocyte marker CD45. Confirm the absence of , and confirm that the trapped red color is epithelial tumor cells (Momburg F, et al., Immunohistochemical study of the expression of a Mr 34,000 human epithelium-specific surface glycoprotein in normal and malignant tissues ( Immunohistochemical study of expression of 34,000 human male epithelium-specific surface glycoproteins in normal and malignant tissues). Cancer Res. 1987;47:2883-2891; and Allard WJ, et al., Tumor cells. circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases no). Clin Cancer Res. 2004; 10:6897-6904). The number of trapped cells has previously been shown to have prognostic significance for breast, colorectal, and prostate cancer patients with advanced disease (Cohen SJ, et al., J Clin 2008;26:3213-3221; Cristofanilli M, et al. N Engl J Med. 2004;351:781-791; Cristofanilli M, et al., J Clin Oncol. Bono JS, et al. Clin Cancer Res. 2008; 14:6302-6309).

The present invention also provides for isolating CTCs with CTC chip technology. The CTC chip is a microfluidic CTC capture device in which blood flows through a chamber containing thousands of microposts coated with anti-EpCAM antibodies to which CTCs bind (Nagrath S, et al. Isolation of rare circulating tumor cells in cancer patients by microchip technology. Nature. 2007;450: 1235-1239). The CTC chip significantly increased CTC count and purity compared to the CellSearch® system (Maheswaran S, et al. Detection of mutations in EGFR in circulating lung-cancer cells). detection), N Engl J Med. 2008;359:366-377), both platforms may be used for downstream molecular analysis.

cell-free chromatin

In certain embodiments, cell-free chromatin fragments are isolated and analyzed according to the present invention. Nucleosomes may be detected in the serum of healthy individuals and individuals afflicted with disease states (Stroun et al., Annals of the New York Academy of Sciences 906: 161-168 (2000)). Serum concentrations of nucleosomes are also significantly elevated in patients with benign and malignant diseases such as cancer and autoimmune diseases (Holdenrieder et al (2001) Int J Cancer 95, 114-120, Trejo -Becerril et al (2003) Int J Cancer 104, 663-668; Kuroi et al 1999 Breast Cancer 6, 361-364; Kuroi et al (2001) Int j Oncology 19, 143-148; Amoura et al (1997) Arth Rheum 40, 2217-2225; Williams et al (2001) J Rheumatol 28, 81-94). Without being bound by any theory, the high concentration of nucleosomes in patients with tumors is derived from apoptosis. Apoptosis occurs naturally in growing tumors. Nucleosomes that circulate in the blood contain uniquely modified histones. For example, US Patent Publication No. 2005/0069931 (March 31, 2005) relates to the use of antibodies directed to specific histone N-terminal modifications as diagnostic indicators of disease. This use uses such histone-specific antibodies to isolate nucleosomes from patient blood or serum samples to facilitate purification and analysis of accompanying DNA for diagnostic/selection purposes. Thus, the present invention may use chromatin-bound DNA to detect and monitor tumor mutations, for example. Identification of DNA associated with modified histones can serve as diagnostic markers for disease and congenital defects.

Thus, in other embodiments, the isolated chromatin fragment is derived from circulating chromatin, preferably circulating mono- and oligonucleosomes. An isolated chromatin fragment may be derived from a biological sample. A biological sample may be derived from a subject or patient in need thereof. A biological sample may be serum, plasma, lymph, blood, blood fractions, urine, synovial fluid, spinal fluid, saliva, circulating tumor cells, or mucus.

Cell-free DNA (cfDNA)

In certain aspects, the present invention may be used to detect cell-free DNA (cfDNA). Cell-free DNA in plasma or serum may be used as a non-invasive diagnostic tool. For example, cell-free fetal DNA has been studied and optimized for testing for compatible RhD factors, sex determination for X-linked latent genetic disorders, monogenic disorder testing, and preeclampsia identification. For example, sequencing the cfDNA of the fetal cellular fraction in maternal plasma is a reliable method of detecting copy number alterations associated with fetal chromosomal aneuploidy. As another example, cfDNA isolated from cancer patients is used to detect mutations in key genes relevant to treatment decisions.

In certain exemplary embodiments, the present disclosure provides for detecting cfDNA directly from patient samples. In certain other exemplary embodiments, the present disclosure provides for enriching the cfDNA using the enrichment embodiments disclosed above prior to detecting the target cfDNA.

exosome

In one aspect, exosomes may be assayed according to the present invention. Exosomes are small extracellular vesicles that have been shown to contain RNA. Isolation of exosomes by ultracentrifugation, filtration, chemical precipitation, size exclusion chromatography, and microfluidics are known in the art. In one aspect, an exosome is purified using an exosome biomarker. Isolation and purification of exosomes from biological samples may be performed by any known method (see, eg, WO2016172598A1).

SNP detection and genotyping

In certain aspects, the present invention may be used to detect the presence of single nucleotide polymorphisms (SNPs) in a biological sample. SNPs may be associated with maternal testing (eg, sex determination, fetal defects). These may be related to criminal investigations. In one aspect, suspects in criminal investigations may be identified by the present invention. Without wishing to be bound by any theory, nucleic acid-based forensic evidence is the highest available for detecting a suspect's or victim's genetic material, as the samples to be tested may be limited. Sensitive assays may be required.

In other embodiments, SNPs associated with disease are encompassed by the present invention. Disease-associated SNPs are well known in the art, and those skilled in the art can use the methods described above to design suitable guide RNAs (e.g., www.ncbi.nlm.nih.gov/ clinvar?term=human%5Borgn%5D).

In one aspect, the invention relates to methods of genotyping, such as SNP genotyping. The method includes:
distributing a sample or set of samples into one or more discrete volumes containing a CRISPR system according to the invention described herein;
incubating said sample or said set of samples under conditions sufficient to allow said one or more guide RNAs to bind to one or more target molecules;
activating a CRISPR effector protein by binding of said one or more guide RNAs to one or more target molecules, wherein activation of the CRISPR effector protein produces a detectable positive signal; the RNA-based masking construct is modified); and detecting a detectable positive signal, wherein said detectable positive signal is one or more target molecules specific to a particular genotype in a sample. is present).

In certain aspects, for example, as shown in the embodiment of FIG. 60, the detectable signal is compared (eg, by comparing signal strength) to one or more reference signals, preferably a synthetic reference signal. In certain embodiments, the criterion is or corresponds to a particular genotype. In certain aspects, the criteria include specific SNPs or other (single) nucleotide diversity. In certain aspects, the reference is a (PCR amplified) genotypic reference. In certain aspects, the reference is or comprises DNA. In certain aspects, the reference is or comprises RNA. In certain aspects, the reference is or comprises RNA transcribed from DNA. In certain aspects, the reference is or comprises DNA reverse transcribed from RNA. In certain aspects, the detectable signal is compared to one or more criteria each corresponding to a known genotype, such as a SNP or other (single) nucleotide diversity. In certain aspects, the detectable signal is compared to one or more reference signals, the comparison including, for example, statistical analysis by parametric or non-parametric statistical analysis (eg, one-way or two-way analysis of variance, etc.). In certain aspects, the detectable signal is compared to one or more reference signals, and if the detectable signal does not deviate significantly (statistically) from the reference, the genotype is identified as the genotype corresponding to said reference. It is determined.

In other embodiments, the present invention enables rapid genotyping for emergency pharmacogenomics. In one aspect, a point-of-care assay may be used to determine the genotype of a patient presented to the emergency room. A patient may be suspected of having a blood clot and the emergency physician should determine the dosage of anticoagulant. In exemplary embodiments, the invention may provide guidance for administration of anticoagulants during treatment of myocardial infarction or stroke based on genotyping markers such as VKORC1, CYP2C9, and CYP2C19. good. In one aspect, the anticoagulant is the anticoagulant warfarin (Holford, NH (December 1986). "Clinical Pharmacokinetics and Pharmacodynamics of Warfarin Understanding the Dose-Effect Relationship." Clinical Pharmacokinetics and Pharmacology of Warfarin". Clinical Pharmacokinetics. Springer International Publishing. 11 (6): 483-504). Genes associated with thrombus are known in the art (e.g. US20060166239A1; Litin SC, Gastineau DA (1995) "Current concepts in anticoagulant therapy". Mayo Clin. Proc 70 (3): 266-72; and Rusdiana et al., Responsiveness to low-dose warfarin associated with genetic variants of VKORC1, CYP2C9, CYP2C19, and CYP4F2 in an Indonesian population. Responsiveness to low-dose warfarin associated with genetic variants in CYP4F2). Eur J Clin Pharmacol. 2013 Mar;69(3):395-405). Specifically, the VKORC1 1639 (or 3673) single nucleotide polymorphism replaces the common (“wild-type”) G allele with an A allele. People with the A allele (or "A haplotype") produce less VKORC1 than people with the G allele (or "non-A haplotype"). The prevalence of these variants also varies by race, with 37% of Caucasians and 14% of Africans carrying the A allele. The end result is a reduction in the number of blood clotting factors and thus a reduction in blood clotting capacity.

In certain exemplary embodiments, the availability of genetic material for detecting SNPs in patients allows SNPs to be detected without amplifying DNA or RNA samples. For genotyping, the biological sample to be tested can be readily obtained. In certain exemplary embodiments, the incubation time of the present invention may be shortened. Assays may be performed for as long as necessary for the enzymatic reaction to occur. One skilled in the art may perform a 5 minute biochemical reaction (eg, 5 minute ligation). The present invention may obtain DNA from blood using an automated DNA extractor. DNA may then be added to the reaction to generate the target molecule for the effector protein. Immediately after generation of the target molecule, the masking factor may be cleaved and the signal detected. In an exemplary embodiment, the present invention enables rapid diagnosis of POC by genotyping prior to administering drugs (eg, anticoagulants). When an amplification step is used, all reactions occur in the same reaction over the course of one step. In preferred embodiments, the POC assay may be performed in less than 1 hour, preferably within 10, 20, 30, 40, or 50 minutes.

In certain aspects, the systems, devices, and methods disclosed herein may be used to detect the presence or abundance of long non-coding region RNAs (lncRNAs). Expression of specific lncRNAs is associated with disease states and/or drug resistance.特に、特定のｌｎｃＲＮＡ（例えば、TCONS_00011252、NR_034078、TCONS_00010506、TCONS_00026344、TCONS_00015940、TCONS_00028298、TCONS_00026380、TCONS_0009861、TCONS_00026521、TCONS_00016127、NR_125939、NR_033834、TCONS_00021026、TCONS_00006579、NR_109890、および NR_026873）は癌治療に対する耐性、例えば、黒色tumor (e.g., nodular melanoma, malignant lentigo, malignant lentiginous melanoma, acral lentiginous melanoma, superficial spreading melanoma, mucosal melanoma, polypoid melanoma, desmoplastic melanoma, hypomelanotic melanoma) associated with resistance to one or more BRAF inhibitors (eg, vemurafenib, dabrafenib, sorafenib, GDC-0879, PLX-4720, and LGX818) to treat cervical cancer, and soft tissue melanoma. Detection of lncRNAs using various embodiments described herein may facilitate diagnosis of disease and/or selection of treatment options.

In one aspect, the invention can lead to DNA- or RNA-targeted therapies (eg, CRISPR, TALE, zinc finger proteins, RNAi), especially when rapid delivery of therapy is critical to therapeutic outcome.

Detection of LOH

Cancer cells suffer loss of genetic material (DNA) compared to normal cells. This loss of genetic material is termed "loss of heterozygosity" (LOH) and is suffered by most, if not all, cancers. Loss of heterozygosity (LOH) is a chromosome-wide event resulting in loss of the entire gene and surrounding chromosomal regions. Loss of heterozygosity is a common occurrence in cancer and may indicate the absence of functional tumor suppressor genes in the lost regions. However, disappearance can be silent. This is because one functional gene still remains on the other chromosome of the chromosome pair. The remaining copy of the tumor suppressor gene can be inactivated by point mutations, leading to loss of the tumor suppressor gene. Depletion of genetic material from cancer cells may selectively eliminate one of two or more alleles of a gene essential for cell viability or cell growth at a particular chromosomal locus.

A "LOH marker" is DNA derived from a microsatellite locus whose deletion, alteration, or amplification, compared to normal cells, is associated with cancer or other diseases. LOH markers are often associated with tumor suppressor genes or other genes commonly associated with tumors.

The term "microsatellite" refers to short repetitive sequences of DNA that are widely distributed in the human genome. Microsatellites are groups of tandemly repeated (ie contiguous) DNA motifs ranging in length from 2-5 nucleotides, typically repeated 5-50 times. For example, the sequence TATATATATA (SEQ ID NO: 418) is a dinucleotide microsatellite and GTCGTCGTCGTCGTC (SEQ ID NO: 419) is a trinucleotide microsatellite (where A is adenine, G is guanine, C is cytosine, T is thymine). Somatic mutations of such microsatellite repeat lengths have been shown to represent tumor-specific features. Guide RNAs may be designed to detect such microsatellites. Additionally, the present invention may be used to detect repeat length changes, amplifications and deletions based on quantification of the detectable signal. Certain microsatellites are located in the regulatory flanking or intronic regions of genes, or directly at codons of genes. Microsatellite mutations in such cases can lead to phenotypic changes and diseases, particularly triplet (3 nucleotide pairs) repeat expansion diseases such as fragile X syndrome and Huntington's disease.

Frequent loss of heterozygosity (LOH) at specific chromosomal regions has been reported in many types of malignancies. Allelic loss at specific chromosomal regions is the most common genetic alteration observed in a variety of malignancies, and thus samples from body fluids (e.g., saliva for lung cancer, urine for bladder cancer) were analyzed using microsatellite analysis. (Rouleau, et al. Nature 363, 515-521 (1993); and Latif, et al. Science 260, 1317-1320 (1993)). It has also been established that significantly elevated concentrations of soluble DNA are found in the plasma of individuals with cancer and some other diseases. This indicates that cell-free serum or plasma may be used to detect cancer DNA through microsatellite aberrations (Kamp, et al. Science 264, 436-440 (1994); and Steck, et al. Nat Genet. 15(4), 356-362 (1997)). Two groups have reported microsatellite changes in plasma or serum of a limited number of patients with small cell lung cancer or head and neck cancer (Hahn, et al. Science 271, 350-353 ( 1996); and Miozzo, et al. Cancer Res. 56, 2285-2288 (1996)). Detection of loss of heterozygosity in sera of tumor and melanoma patients has been previously demonstrated (eg US Pat. No. 6,465,177 B1).

Therefore, it would be advantageous to detect LOH markers in a subject having or at risk of having cancer. The present invention may be used to detect LOH in tumor cells. In one aspect, circulating tumor cells may be used as the biological sample. In preferred embodiments, cell-free DNA from serum or plasma is used to non-invasively detect and/or monitor LOH. In other embodiments, the biological sample can be any sample described herein (eg, urine sample for bladder cancer). Without being bound by any theory, the present invention may be used to detect LOH markers with improved sensitivity compared to any conventional method, thereby providing early detection of mutational events. In one aspect, LOH is detected in bodily fluids. In this case, the presence of LOH is associated with the development of cancer. The methods and systems described herein provide a non-invasive, rapid, and accurate method of detecting LOH of specific alleles associated with cancer, allowing conventional methods such as PCR or tissue biopsies to It represents a significant advantage over technology. Thus, the present invention provides methods and methods that may be used to screen for high-risk populations and monitor high-risk patients undergoing chemoprophylaxis, chemotherapy, immunotherapy, or other treatments. provide the system.

Since the method of the invention only requires the extraction of DNA from bodily fluids such as blood, it may be repeated at any given time in a single patient. Blood is drawn for follow-up tests for disease progression, stability, or recurrence before, during, or after surgery, chemotherapy, radiation therapy, gene therapy, or immunotherapy, or after treatment. may be used to monitor LOH. Without being bound by any theory, because LOH markers are specific to an individual patient's tumor, the methods of the invention can be used to determine the presence or absence of subclinical disease by LOH markers specific to that patient. Recurrence may be detected. The method may also detect whether multiple metastases are present using a tumor-specific LOH marker.
Detection of epigenetic modifications

Histone variants, DNA modifications, and histone modifications that are indicative of cancer or cancer progression may be used in the present invention. For example, US Patent Publication No. 20140206014 describes elevated amounts of nucleosomal H2AZ, macroH2A1.1, 5-methylcytosine, P-H2AX (Ser139) in cancer samples compared to healthy subjects. It is When cancer cells are present in an individual, increased apoptosis of the cancer cells may result in increased production of cell-free nucleosomes in the blood. In one aspect, antibodies against marks associated with apoptosis, such as H2B Ser 14(P), may be used to identify single nucleosomes released from apoptotic neoplastic cells. Therefore, preferably, DNA generated from tumor cells may be analyzed with high sensitivity and precision according to the present invention.

prenatal screening

In certain aspects, the methods and systems of the present invention may be used in prenatal screening. In certain aspects, circulating cell-free DNA is used in prenatal selection methods. In certain aspects, DNA associated with single nucleosomes or oligonucleosomes may be detected with the present invention. In a preferred embodiment, detection of single-nucleosome or oligonucleosome-associated DNA is used for prenatal screening. In certain embodiments, cell-free chromatin fragments are used in prenatal selection methods.

Prenatal diagnosis or prenatal screening refers to testing a fetus or embryo for a disease or condition before it is born. This purpose includes neural tube defects, Down's syndrome, chromosomal abnormalities, genetic disorders, and other diseases (e.g., spina bifida, cleft palate, Tay-Sachs disease, sickle cell anemia, thalassemia, cystic fibrosis, muscular dystrophy, and fragile X syndrome). Screening may also be used for prenatal sex determination. Common testing procedures include amniocentesis, ultrasonography including nuchal translucency, serum marker testing, or genetic screening. In some cases, tests are given to decide whether to terminate the fetus, but doctors and patients should be able to diagnose high-risk pregnancies early and send them to specialized hospitals where the newborn can receive appropriate care. They see it as useful because it allows them to plan their births.

It is understood that there are fetal cells present in the mother's blood and that these cells represent a potential source of fetal chromosomes for prenatal DNA diagnostics. Also, fetal DNA ranges from about 2-10% of the total DNA in maternal blood. Currently available prenatal genetic tests generally involve invasive procedures. For example, chorionic villus sampling (CVS) performed on a pregnant woman at about 10-12 weeks gestation and amniocentesis performed at about 14-16 weeks are all invasive procedures for obtaining samples for fetal chromosomal aberration testing. Contains procedures. Fetal cells obtained via these collection procedures are usually tested for chromosomal abnormalities using cytogenetic or fluorescence in situ hybridization (FISH) analysis. Cell-free fetal DNA has been found to be present in the plasma and serum of pregnant women as early as the sixth week of pregnancy, with concentrations increasing during pregnancy and peaking before birth. Since these cells appear very early in pregnancy, they can form the basis of an accurate non-invasive first-trimester test. Without being bound by any theory, the present invention provides unprecedented sensitivity to detect small amounts of fetal DNA. Without being bound by any theory, abundant amounts of maternal DNA are generally co-recovered with the subject's fetal DNA, thus reducing sensitivity in fetal DNA quantification and mutation detection. . The present invention overcomes such problems due to the unexpected high sensitivity of the assay.

The H3 class of histones consists of four distinct protein species: major forms H3.1 and H3.2, substitution form H3.3, and testis-specific variant H3t. H3.1 and H3.2 are closely related but differ only at Ser96. H3.1 differs from H3.3 at at least 5 amino acid positions. In addition, H3.1 is highly abundant in fetal liver compared to its presence in adult tissues, including liver, kidney, and heart. In adult human tissue, H3.3 variants are more common than H3.1 variants, but the opposite is true in fetal liver. The present invention may use these differences to detect fetal nucleosomes and fetal nucleic acids in maternal biological samples containing both fetal and maternal cells and/or fetal nucleic acids.

In one aspect, fetal nucleosomes may be obtained from blood. In other embodiments, fetal nucleosomes may be obtained from a cervical mucus sample. In certain embodiments, the cervical mucus sample is obtained by swabbing or washing a pregnant woman in the early second or late first trimester of pregnancy. The sample may be placed in an incubator to release the mucus-trapped DNA. The incubator may be set at 37°C. The sample may be rocked for about 15-30 minutes. The mucus may be further lysed with a mucinase to release the DNA. The sample may be exposed to conditions such as chemical treatments or treatments known in the art to induce apoptosis and release fetal nucleosomes. Thus, cervical mucus samples may be treated with agents that induce apoptosis, thereby releasing fetal nucleosomes. See US Patent Publication Nos. 20070243549 and 20100240054 for enrichment of circulating fetal DNA. The present invention is of particular advantage in applying the method and system to prenatal selection where only a small fraction of nucleosomes or DNA is of fetal origin.

Antenatal selection according to the present invention includes, but is not limited to, trisomy 13, trisomy 16, trisomy 18, Klinefelter's syndrome (47, XXY), (47, XYY) and (47, XXX), Turner's syndrome, Down's syndrome (trisomy 21), cystic fibrosis, Huntington's disease, beta thalassemia, myotonic dystrophy, sickle cell anemia, porphyria, fragile X syndrome, Robertsonian translocation, Angelman's syndrome , DiGeorge syndrome, and Wolf-Hirschhorn syndrome.

Further aspects of the present invention are directed to a wide range of genetic disorders further described under the heading "Genetic Disorders" on the National Institutes of Health website (website: health.nih.gov/topic/Genetic Disorders). It relates to diagnosing, prognosticating and/or treating associated defects.

Detection of cancer and cancer drug resistance

In certain embodiments, the present invention may be used to detect genes and mutations associated with cancer. In certain aspects, mutations associated with resistance are detected. During treatment, resistant tumor cells may be amplified in clonal populations of tumor cells, or resistance mutations may emerge (e.g., Burger JA, et al., Clonal evolution in patients with chronic lymphocytic leukemia developing resistance to BTK inhibition). 2016 May 20;7:11589; Landau DA, et al., Mutations driving CLL and their evolution in progression and relapse. Nature. 2015 Oct 22;526(7574):525-30; Landau DA, et al., Clonal evolution in hematological malignancies and therapeutic implications. Leukemia. 2014 Jan;28(1):34 -43; and Landau DA, et al., Evolution and impact of subclonal mutations in chronic lymphocytic leukemia. Cell. 2013 Feb 14;152(4):714-26 checking). Therefore, detecting such mutations requires very sensitive assays and monitoring requires repeat biopsies. Repeated biopsies are inconvenient, invasive and costly. Resistance mutations can be difficult to detect in blood samples or biological samples (e.g., blood, saliva, urine) collected by other non-invasive methods using conventional methods known in the art. . Resistance mutations may refer to mutations associated with resistance to chemotherapy, targeted therapy, or immunotherapy.

In certain embodiments, mutations occur in individual cancers and may be used to detect cancer progression. In one aspect, mutations related to T cell cytolytic activity against tumors have been characterized by the present invention and may be detected (e.g., Rooney et al., Molecular and genetic properties of tumors associated with local immune cytolytic activity ( Molecular and genetic features of tumors associated with local immune cytolytic activity), Cell. 2015 January 15; 160(1-2): 48-61). Individualized therapies may be developed based on detection of these mutations (see, eg, WO2016100975A1). In certain aspects, cancer-specific mutations associated with cytolytic activity are CASP8, B2M, PIK3CA, SMC1A, ARID5B, TET2, ALPK2, COL5A1, TP53, DNER, NCOR1, MORC4, CIC, IRF6, MYOCD, from ANKLE1, CNKSR1, NF1, SOS1, ARID2, CUL4B, DDX3X, FUBP1, TCP11L2, HLA-A, B, or C, CSNK2A1, MET, ASXL1, PD-L1, PD-L2, IDO1, IDO2, ALOX12B, and ALOX15B Chromosome bands 6q16.1-q21, 6q22.31-q24.1, 6q25.1-q26, 7p11.2-q11.1, 8p23. 1, 8p11.23-p11.21 (including IDO1 and IDO2), 9p24.2-p23 (including PDL1 and PDL2), 10p15.3, 10p15.1-p13, 11p14.1, 12p13.32-p13. 2, 17p13.1 (including ALOX12B, ALOX15B), and 22q11.1-q11.21.

In certain embodiments, the invention is used to detect cancer mutations (e.g., resistance mutations) during or after treatment has been completed. Disease recurrence can be detected.

In certain exemplary embodiments, detection of miRNA signatures of microRNAs (miRNAs) and/or of differentially expressed miRNAs is used to detect or monitor cancer progression and/or drug resistance to cancer treatments. may be detected. As an example, Nadal et al. (Nature Scientific Reports, (2015) doi:10.1038/srep12464) describe mRNA signatures, which may be used to detect non-small cell lung cancer (NSCLC).

In certain exemplary embodiments, the presence of resistance mutations in clonal subpopulations of cells may be used to determine treatment regimens. In other embodiments, individualized therapies may be administered that treat patients based on common tumor mutations. In certain aspects, common mutations develop in response to therapy leading to drug resistance. In certain embodiments, the present invention may be used to monitor patients for the expansion of cells that have acquired mutations or harbor such drug resistance mutations.

Treatment with various chemotherapeutic agents, especially targeted therapeutic agents such as tyrosine kinase inhibitors, often leads to de novo mutations in target molecules that resist the activity of therapy. Multiple strategies to overcome this resistance are being evaluated, for example, the development of second-generation therapeutics that are unaffected by these mutations, and multidrug therapy, including those that act downstream of resistance mutations. there is In one exemplary embodiment, a common mutation for ibrutinib, a molecule that targets Bruton's Tyrosine Kinase (BTK) and is used against CLL and certain lymphomas, is from a cysteine at position 481 (BTK/C481S) to It is a change to serine. Erlotinib, which targets the tyrosine kinase domain of the epidermal growth factor receptor (EGFR), is commonly used to treat lung cancer, but resistant tumors invariably develop after treatment. A common mutation found in resistant clones is a threonine to methionine mutation at position 790.

Non-silencing mutations shared in cancer patient populations and common resistance mutations that can be detected with the present invention are known in the art (see, eg, WO/2016/187508). In certain aspects, drug resistance mutations may be induced by treatment with ibrutinib, erlotinib, imatinib, gefitinib, crizotinib, trastuzumab, vemurafenib, RAF/MEK, immune checkpoint inhibition therapy, or anti-estrogen therapy. In certain aspects, the cancer-specific mutation is programmed death ligand 1 (PD-L1), androgen receptor (AR), Bruton's Tyrosine Kinase (BTK), epidermal growth factor receptor (EGFR), BCR- one or more genes encoding proteins selected from the group consisting of Abl, c-kit, PIK3CA, HER2, EML4-ALK, KRAS, ALK, ROS1, AKT1, BRAF, MEK1, MEK2, NRAS, RAC1, and ESR1 exists in

Immune checkpoints are inhibitory pathways that slow and stop the immune response and prevent excessive tissue damage from uncontrolled activation of immune cells. In particular aspects, the targeted immune checkpoint is the programmed death-1 (PD-1 or CD279) gene (PDCD1). In other embodiments, the targeted immune checkpoint is cytotoxic T-lymphocyte-associated antigen (CTLA-4). In further embodiments, the immune checkpoints targeted are CD28 and others of the CTLA4 Ig superfamily (eg, BTLA, LAG3, ICOS, PDL1, or KIR). In further embodiments, the targeted immune checkpoint is one of the TNFR superfamily (eg, CD40, OX40, CD137, GITR, CD27, or TIM-3).

Recently, the expression of genes in tumors and their microenvironment has been characterized at the single-cell level (e.g. Tirosh, et al. Dissecting the multicellular ecosystem of metastatic melanoma by single cell RNA-seq). Science 352, 189-196, doi:10.1126/science.aad0501 (2016)); Tirosh et al., Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma. 2016 Nov 10;539(7628):309-313. doi : 10.1038/nature20123. Epub 2016 Nov 2; and International Patent Publication WO2017004153. (see A1). In certain embodiments, the present invention may be used to detect genetic signatures. In one aspect, complement genes are monitored or detected in the tumor microenvironment. In one aspect, MITF and AXL programs are monitored or detected. In one aspect, tumor-specific stem or progenitor cell characteristics are detected. Such features are indicative of immune response status and tumor status. In certain embodiments, tumor status with respect to growth, resistance to therapy, and abundance of immune cells may be detected.

Thus, in certain embodiments, the present invention provides a low-cost, rapid, multiplexed cancer detection panel for circulating DNA, such as tumor DNA, particularly for monitoring disease recurrence or the development of common resistance mutations.

Application of immunotherapy

Embodiments disclosed herein may also be useful in the context of additional immunotherapeutic methods. For example, in some embodiments, a method of diagnosing, predicting, and/or staging an immune response in a subject comprises detecting a first expression level, activity and/or function of one or more biomarkers; Including comparing the detected amount to a control amount. Here, a difference between the detected amount and the control amount indicates that the subject has an immune response.

In certain aspects, the present invention may be used to determine tumor infiltrating lymphocyte (TIL) dysfunction or activation. TILs may be isolated using known methods. TILs may be analyzed to determine whether they are used for adoptive cell transfer therapy. Chimeric antigen receptor T-cells (CAR-T-cells) may also be analyzed for characteristics of dysfunction or activation prior to administration to a subject. Exemplary characteristics of dysfunctional and activated T cells have been described (see, e.g., Singer M, et al., A Distinct Gene Module for Dysfunction Uncoupled from Activation in Tumor-Infiltrating T Cells). Individual Gene Modules for Dysfunction Disconnected from Cell. Cell. 2016 Sep 8;166(6):1500-1511.e9.

In some embodiments, C2c2 may be used to assess the status of immune cells, eg, T cells (eg, CD8 ⁺ and/or CD4 ⁺ T cells). In particular, T cell activation and/or dysfunction may be determined, for example, based on genes or genetic signatures associated with one or more T cell conditions. Thus, c2c2 may be used to determine the presence of T cells in one or more subpopulations.

In some embodiments, C2c2 may be used in diagnostic assays or as a method of determining whether a patient is suitable for immunotherapy or other types of treatment. For example, detection of genetic or biomarker features may be performed by c2c2 to determine whether a patient is responding to a given therapy or whether it is due to T cell dysfunction. Such detection is informative regarding the type of therapy that is most suitable for a patient to receive. For example, whether the patient will receive immunotherapy.

In some embodiments, the systems and assays disclosed herein determine whether a patient's response to therapy (e.g., adoptive cell transfer (ACT) therapy) is due to cellular dysfunction and, if so, across biomarker characteristics. The amount of up-regulation and down-regulation allows the clinician to identify whether the problem can be treated. For example, if a patient undergoing ACT does not respond, the cells administered as part of ACT can be assayed by assays disclosed herein to correlate with cell activation and/or dysfunctional states. A relative amount of expression of a known biomarker feature may be determined. If a particular inhibitory receptor or molecule is upregulated on ACT cells, the patient may be treated with an inhibitor of that receptor or molecule. If a particular stimulatory receptor or molecule is down-regulated in ACT cells, the patient may be treated with agonists of that receptor or molecule.

In certain exemplary embodiments, the systems, methods, and devices described herein may be used to screen for genetic signatures that identify particular cell types, cell phenotypes, or cell states. . Similarly, the embodiments disclosed herein may be used to detect the transcriptome using methods such as compressed sensing. Gene expression data are highly structured such that the expression levels of some genes predict the expression levels of other genes. With the knowledge that gene expression data are highly structured, it can be assumed that the number of degrees of freedom of the system is reduced. This ensures a sparse basis for calculating relative gene abundance. It is possible to make some biologically motivated assumptions whereby undersampling without any specific knowledge of what the genes are interacting with, we propose a non-linear interaction relationship can be restored. In particular, if we assume that the gene interactions are low-rank, sparse, or a combination thereof, the true number of degrees of freedom is small for a perfect combinatorial extension. This allows us to infer a fully non-linear landscape with a relatively small number of perturbations. With these assumptions, we may design undersampled combinatorial perturbation experiments using analytical theory of matrix completion and compressed sensing. Undersampling may also be employed by building predictors of combinatorial perturbations without directly learning any individual interaction coefficients using a kernel learning framework. Compressive sensing provides a way to identify a minimal number of target transcripts to detect in order to obtain a comprehensive gene expression profile. Compressed sensing methods are disclosed in PCT/US2016/059230 (“Systems and Methods for Determining Relative Abundances of Biomolecules”) filed Oct. 27, 2016. , the contents of which are incorporated herein by reference. When methods such as compression sensing are used to identify a minimal set of transcript targets, a corresponding set of guide RNAs may be designed to detect said transcripts. Thus, in certain exemplary embodiments, a method of obtaining a gene expression profile of a cell, using the embodiments disclosed herein, provides a gene expression profile of a single cell or a population of cells. of the set of transcripts.

Detects tagged nucleic acids

Alternatively, nucleic acid identifiers may be detected using embodiments described herein. A nucleic acid identifier is a non-coding region nucleic acid that may be used to identify a particular item. Exemplary nucleic acid identifiers (eg, DNA watermarks) are described in Heider and Barnekow. "DNA watermarks: A proof of concept," BMC Molecular Biology 9:40 (2008). It is Alternatively, the nucleic acid identifier may be a nucleic acid barcode. Nucleic acid-based barcodes are short sequences of nucleotides (eg, DNA, RNA, or combinations thereof) that are used as identifiers for associated molecules (eg, target molecules and/or target nucleic acids). Nucleic acid barcodes are at least in length, e.g. 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, 60, 70, 80, 90, or 100 nucleotides, in single- or double-stranded form may be One or more nucleic acid barcodes may be attached to, or "tagged", a target molecule and/or target nucleic acid. This binding may be direct (e.g., covalent or non-covalent binding of the barcode to the target molecule) or indirect (e.g., using a specific binding agent such as an antibody (or other protein), etc.). , via an additional molecule) or via a barcode-receptive adapter (or other nucleic acid molecule). Target molecules and/or target nucleic acids may be labeled with multiple nucleic acid barcodes in combination (such as nucleic acid barcode concatenated intermediates). Nucleic acid barcodes are typically used to indicate that they are derived from specific compartments (e.g., discrete volumes), have specific physical properties (e.g., affinity, length, sequence, etc.), or have specific therapeutic conditions. A target molecule and/or target nucleic acid is identified as subject. A target molecule and/or target nucleic acid may be associated with multiple nucleic acid barcodes to provide information on all of these characteristics (and more). Methods of generating nucleic acid barcodes are disclosed, for example, in International Patent Application Publication No. WO/2014/047561.

enzyme

The present application further provides orthologues of C2c2 that exhibit robust activity that are particularly suitable for different applications of RNA cleavage and detection. These uses include, but are not limited to, those described herein. More particularly, the orthologue shown to have stronger activity than others tested is the C2c2 orthologue identified from the organism Leptotorichia weedii (LwC2c2). Accordingly, the present application provides methods of modifying a target locus of interest. Said method comprises producing a non-naturally occurring or genetically engineered composition comprising a C2c2 effector protein, particularly a C2c2 effector protein with enhanced activity as described herein, and one or more nucleic acid components. Including delivering to a sitting position. Here, at least said one or more nucleic acid moieties are genetically engineered to direct the complex to a target of interest. The effector protein forms a complex with the one or more nucleic acid moieties, and the complex binds to the target locus of interest. In certain embodiments, the target locus of interest comprises RNA. The present application relates to RNA sequence-specific interference, RNA sequence-specific gene regulation, screening of RNA or RNA products, lincRNA, non-coding region RNA, nuclear RNA, or mRNA, mutagenesis, fluorescent in situ Further provided is the use of the Cc2 effector protein with enhanced activity in hybridization or propagation.

Embodiments disclosed herein may also be performed using a lateral flow assay. Such assays are described in U.S. Provisional Patent Application Nos. 62/568,309; 62/610,144 and 62/623,529, and Gootenberg et al. disclosed.

Further embodiments of the invention are described in the following numbered paragraphs.
1. A nucleic acid detection system comprising a CRISPR system comprising one or more guide RNAs designed to bind to an effector protein and a corresponding target molecule; and an RNA-based masking construct.
2. a CRISPR system comprising one or more guide RNAs designed to bind to effector proteins, trigger RNAs;
A polypeptide detection system comprising an RNA-based masking construct; and one or more detection aptamers comprising a masked RNA polymerase promoter binding site or a masked primer binding site.
3. The system of paragraphs 1 or 2, further comprising nucleic acid amplification reagents.
4. The system of paragraph 1, wherein said target molecule is target DNA, said system further comprising a primer that binds to target DNA and comprises an RNA polymerase promoter.
5. The system of any one of paragraphs 1-4, wherein the CRISPR system effector protein is an RNA target effector protein.
6. 6. The system of paragraph 5, wherein said RNA target effector protein comprises one or more HEPN domains.
7. 7. The system of paragraph 6, wherein said one or more HEPN domains comprise a RxxxxH motif sequence.
8. The system of paragraph 7, wherein said RxxxH motif comprises a R{N/H/K]X1X2X3H sequence.
9. X1 is R, S, D, E, Q, N, G, or Y; X2 is independently I, S, T, V, or L; X3 is independently L, F, N, 9. The system of paragraph 8 that is Y, V, I, S, D, E, or A.
10. 10. The system of any one of paragraphs 1-9, wherein the CRISPR RNA target effector protein is C2c2.
11. 7. The system of paragraph 6, wherein said CRISPR RNA target effector protein is C2c2.
12. 12. The system of paragraph 11, wherein said C2c2 is a 20 kb Casl gene.
13. The C2c2 effector protein is Leptotrichia, Listeria, Corynebacter, Satterella, Legionella, Treponema, Filifactor, Eubacterium, Streptococcus, Lactobacillus, Mycoplasma, Bacteroides, Flaviibola, Flavobacterium, Sphaerocheta, Azospirillum, Gluconacetobacter, Neisseria, 13. The system of paragraph 12, derived from an organism of a genus selected from the group consisting of Rosebria, Parvivacrum, Staphylococcus, Nitratifructor, Mycoplasma, Campylobacter, and Lachnospira.
14. Leptotrichia weedii (Lw2); Listeria seerigeri; Lachnospiraceae MA2020; Lachnospiraceae NK4A179; [Clostridium] Aminophyllum DSM 10710; Gallinarum DSM 4847 (second CRISPR locus); Pardibacter propionisigenes WB4; Listeria weihenstephanensis FSL R9-0317; Listeriaceae FSL M6-0635; 1003; Rhodobacter capsulata R121; Rhodobacter capsulata DE442; and Leptotorichia oral taxon 879 species F0557 strain. Chloroflexus agregans; Demechina aurantiaca; Thalassospira sp. TSL5-1; Pseudobutyrivibrio OR37; Bacteroides ifae; Polyphyromonasaceae KH3CP3RA; Listeria liparia; and Insolitisspirillum peregrinum.
15. The C2c2 effector protein is L. Weedy F0279 or L.I. 15. The system of paragraph 14, which is Weidy F0279(Lw2) C2c2 effector protein.
16. 16. The system of any one of paragraphs 1-15, wherein said RNA-based masking construct suppresses production of a detectable positive signal.
17. 17. The system of paragraph 16, wherein said RNA-based masking construct inhibits production of a detectable positive signal by masking said detectable positive signal or alternatively producing a detectable negative signal.
18. 17. The system of paragraph 16, wherein said RNA-based masking construct comprises a silencing RNA that inhibits production of a gene product encoded by the reporting construct, said gene product producing a detectable positive signal upon expression.
19. 17. The system of paragraph 16, wherein said RNA-based masking construct is a ribozyme that produces said detectable negative signal, and said detectable positive signal is produced upon inactivation of said ribozyme.
20. 20. The system of paragraph 19, wherein said ribozyme converts a substrate to a first color and said substrate changes to a second color upon inactivation of said ribozyme.
21. 17. The system of paragraph 16, wherein said RNA-based masking factor is an RNA aptamer and/or an RNA binding inhibitor.
22. 22. The system of paragraph 21, wherein said aptamer or RNA binding inhibitor sequesters an enzyme and upon acting on a substrate said enzyme produces a detectable signal upon release from said aptamer or RNA binding inhibitor.
23. Said aptamer is an inhibitory aptamer that inhibits an enzyme to prevent said enzyme from catalyzing the production of a detectable signal from a substrate, said RNA binding inhibitor inhibits an enzyme such that said enzyme is a substrate 22. The system of paragraph 21, preventing catalyzing the production of a detectable signal from.
24. 24. The system of paragraph 23, wherein the enzyme is thrombin, horseradish peroxidase, β-galactosidase, or calf alkaline phosphatase.
25. said enzyme is thrombin and said substrate is paranitroanilide covalently linked to a peptide substrate for thrombin or 7-amino-4-methylcoumarin covalently linked to a peptide substrate for thrombin, paragraph 24 system.
26. 22. The system of paragraph 21, wherein said aptamer sequesters a pair of agents that bind to produce a detectable signal upon release from said aptamer.
27. 17. The system of paragraph 16, wherein said RNA-based masking construct comprises an RNA oligonucleotide to which a detectable ligand and masking moiety are attached.
28. The RNA-based masking construct comprises nanoparticles held in aggregate by bridging molecules, at least a portion of the bridging molecules comprising RNA, and the solution changes color as the nanoparticles are distributed in solution. , the system of paragraph 16.
29. 29. The system of paragraph 28, wherein said nanoparticles are colloidal metals.
30. 30. The system of paragraph 29, wherein said colloidal metal is colloidal gold.
31. 17. The system of paragraph 16, wherein said RNA-based masking construct comprises quantum dots bound to one or more quenching molecules by binding molecules, at least a portion of said binding molecules comprising RNA.
32. 17. The system of paragraph 16, wherein said RNA-based masking construct comprises RNA complexed with an intercalating agent, said intercalating agent changing absorbance when said RNA is cleaved.
33. 33. The system of paragraph 32, wherein said intercalating agent is pyronine-Y or methylene blue.
34. 17. The system of paragraph 16, wherein said detectable ligand is a fluorophore and said masking moiety is a quencher molecule.
35. The masking construct comprises an RNA oligonucleotide designed to bind to a guanine quadruplex forming sequence, a guanine quadruplex structure being formed by the guanine quadruplex forming sequence upon cleavage of the masking construct for detection. 17. The system of paragraph 16, producing a possible positive signal.
36. 36. The system of any one of paragraphs 1-35, wherein the one or more guide RNAs designed to bind to corresponding target molecules comprise synthetic mismatches.
37. 37. The system of paragraph 36, wherein said mismatch is upstream or downstream of a SNP or other single nucleotide diversity of said target molecule.
38. 38. The detection system of paragraphs 36 or 37, wherein the synthetic mismatch or single nucleotide diversity of said guide RNA is at position 3, 4, 5 or 6, preferably position 3, of said spacer.
39. 39. Any one of paragraphs 36-38, wherein the synthetic mismatch of the guide RNA is at position 1, 2, 3, 4, 5, 6, 7, 8 or 9, preferably at position 5, of the spacer. detection system.
40. 40. Any one of paragraphs 36-39, wherein said synthetic mismatch is 1, 2, 3, 4 or 5 nucleotides, preferably 2 nucleotides upstream or downstream of a SNP or other single nucleotide diversity of said guide RNA. The detection system described in .
41. 41. The detection system of any one of paragraphs 36-40, wherein the guide RNA comprises a spacer truncated relative to the wild-type spacer.
42. 42. The detection system of paragraph 41, wherein said guide RNA comprises a spacer comprising less than 28 nucleotides, preferably 20-27 nucleotides, inclusive.
43. 43. The detection system of paragraph 42, wherein the guide RNA comprises a spacer consisting of 20-25 nucleotides or 20-23 nucleotides, preferably 20 or 23 nucleotides.
44. 44. The method of any one of paragraphs 1-43, wherein the one or more guide RNAs are designed to detect single nucleotide polymorphisms in target RNA or DNA or to splice variants in RNA transcripts. detection system.
45. A method of detecting a virus in a sample, comprising:
distributing a sample or set of samples into one or more discrete volumes comprising the CRISPR system of any one of paragraphs 1-44;
incubating said sample or said set of samples under conditions sufficient to allow said one or more guide RNAs to bind to one or more target molecules;
activating a CRISPR effector protein by binding of said one or more guide RNAs to one or more target molecules, wherein activation of the CRISPR effector protein produces a detectable positive signal; RNA-based masking construct is modified); and detecting said detectable positive signal, wherein detection of said detectable positive signal indicates the presence of one or more viruses in said sample. A method, including
46. 46. The method of paragraph 45, wherein said sample comprises two or more viruses and said method distinguishes between said two or more viruses.
47. 47. The method of paragraphs 45 or 46, wherein said guide RNA detects single nucleotide variants of said one or more viruses.
48. 48. The method of paragraph 47, wherein said guide RNA comprises one or more synthetic mismatches.
49. 48. The method of any one of paragraphs 45-47, wherein the one or more CRISPR-based guide RNAs each comprise a set of universal viral guide RNAs that detect viruses and/or virus strains in a set of viruses. .
50. 50. The method of paragraph 49, wherein said guide RNA is generated using a population coverage method.
51. A method of detecting a virus, comprising:
exposing the CRISPR system of any one of paragraphs 1-36 to a sample;
binding of said one or more guide RNAs to said one or more microorganism-specific target RNAs or one or more trigger RNAs activates said RNA effector proteins such that a detectable positive signal is produced; and detecting said detectable positive signal, wherein detection of said detectable positive signal indicates the presence of one or more viruses in said sample.
52. 52. The method of paragraph 51, wherein said CRISPR system is on the surface of a substrate and said substrate is exposed to said sample.
53. 53. The method of paragraph 52, wherein the same or different CRISPR systems are applied to a plurality of discrete locations on said substrate.
54. 54. The method of paragraph 53, wherein the same or different CRISPR systems are applied to a plurality of discrete locations on said substrate.
55. 55. The method of any one of paragraphs 52-54, wherein the substrate is a substrate of flexible material.
56. 56. The method of paragraph 55, wherein the flexible material substrate is a paper substrate, a cloth substrate, or a flexible polymer substrate.
57. 55. The method of paragraph 54, wherein said different CRISPR systems detect different microorganisms at each location.
58. The substrate is passively exposed to the sample by temporarily immersing the substrate in the fluid to be collected, applying the fluid to be tested to the substrate, or contacting the surface to be tested with the substrate, paragraph 55 the method of.
59. 59. The method of paragraph 58, wherein said sample is a biological or environmental sample.
60. Said environmental samples include food samples, beverage samples, paper surfaces, cloth surfaces, metal surfaces, wood surfaces, plastic surfaces, soil samples, fresh water samples, waste water samples, saline samples, air or other gases. 60. The method of paragraph 59 obtained from sample exposure, or a combination thereof.
61. The biological sample may be a tissue sample, saliva, blood, plasma, serum, feces, urine, saliva, mucus, lymph, synovial fluid, cerebrospinal fluid, ascites, pleural effusion, seroma, pus, or swab of skin or mucosal surface. 59. The method of paragraph 59 obtained from
62. 62. Any one of paragraphs 59-61, wherein said environmental or biological sample is a raw sample and/or said one or more target molecules have not been purified or amplified from said sample prior to applying said method. The method described in .
63. A method of monitoring viral disease outbreaks and/or progression, comprising:
exposing the CRISPR system of any one of paragraphs 1-36 to a sample;
activating RNA effector proteins by binding said one or more guide RNAs to one or more target molecules comprising non-synonymous viral mutations such that a detectable positive signal is produced; and said detectable A method comprising detecting a positive signal, wherein detection of said detectable positive signal is indicative of the type of virus present in said sample.
64. exposing the CRISPR system comprises placing one or more CRISPR systems in one or more discrete volumes and adding a sample or portion of a sample to the one or more discrete volumes; The method of paragraph 63.
65. A method of screening a sample for viral antigens and/or virus-specific antibodies, comprising:
exposing the CRISPR system of any one of paragraphs 2-36 to a sample, wherein said one or more aptamers bind to one or more viral antigens or one or more virus-specific antibodies; The aptamers encode barcodes that identify the one or more viral antigens or the one or more virus-specific antibodies to which the one or more aptamers bind, and the guide RNA is adapted to detect the barcodes. designed for);
binding of said one or more guide RNAs to said one or more microorganism-specific target RNAs or one or more trigger RNAs activates said RNA effector proteins such that a detectable positive signal is produced; and detecting said detectable positive signal, wherein said detectable positive signal is detected in said sample by the presence of one or more viral antigens or one or more virus-specific antibodies. present).
66. 66. The method of any one of paragraphs 45-65, wherein the virus is a DNA virus.
67. The DNA viruses include Myoviridae, Podoviridae, Siphoviridae, Alloherpesviridae, Herpesviridae (including human herpesvirus and varicella-zoster virus), Marocoherpesviridae, Lipothrixviridae, Rudivirus. Adenoviridae, Amplaviruses, Ascoviridae, Asphaviridae (including African swine fever virus), Baculoviridae, Cicaudaviridae, Clavaviridae, Corticoviridae ), Fuceroviridae, Robroviridae, Guttaviridae, Humanrosaviridae, Iridoviridae, Maseilleviridae, Mimiviridae, Nudiviridae, Nimaviridae, Pandoraviridae, Papillomaviridae, Phycodnaviridae, Plasviridae, Polydnaviridae, Polyomaviridae (including Simian virus 40, JC virus, BK virus), Poxviridae (including cowpox and smallpox), Sphaerolipoviridae ( Sphaerolipoviridae, Tectiviridae, Turriviridae, Dinodnavirus, Salterprovirus, Rhizidovirus, or a combination thereof.
68. 66. The method of any one of paragraphs 45-65, wherein said viral infection is caused by a double-stranded RNA virus, a positive-stranded RNA virus, a negative-stranded RNA virus, a retrovirus, or a combination thereof.
69. Said viruses are Coronaviridae, Picornaviridae, Caliciviridae, Flaviviridae, Togaviridae, Bornaviridae, Filoviridae, Paramyxoviridae, Pneumoviridae, Rhabdoviridae , Arenaviridae, Bunyaviridae, Orthomyxoviridae, or Deltavirus.
70. Said viruses are coronavirus, SARS, poliovirus, rhinovirus, hepatitis A, Norwalk virus, yellow fever virus, West Nile virus, hepatitis C virus, dengue virus, Zika virus, rubella virus, Ross River virus, Sindbis Viruses, Chikungunya virus, Borna virus, Ebola virus, Marble virus, Measles virus, Mumps virus, Nipah virus, Hendra virus, Newcastle disease virus, Human respiratory syncytial virus, Rabies virus, Lassa virus, Hantavirus, Crimea virus 69. The method of paragraph 68, Congo hemorrhagic fever virus, influenza, or hepatitis D virus.
71. A method of detecting one or more microorganisms in a sample, comprising:
A method comprising contacting a sample with a nucleic acid detection system according to any of paragraphs 1-44; and subjecting said contacted sample to a lateral flow immunochromatographic assay.
72. Said nucleic acid detection system comprises an RNA-based masking construct comprising a first molecule and a second molecule, said lateral flow immunochromatographic assay preferably detecting said first molecule at discrete detection sites on the horizontal flow strip surface. and detecting the second molecule.
73. 73. The method according to paragraph 72, wherein said first molecule and said second molecule are detected by binding to an antibody that recognizes said first or second molecule, said binding molecule preferably being detected by a sandwich antibody.
74. said horizontal flow strip comprising an upstream first antibody directed against said first molecule and a downstream second antibody directed against said second molecule, wherein said target nucleic acid is present in said sample; Otherwise, the uncleaved RNA-based masking construct binds to the first antibody, and if the target nucleic acid is present in the sample, the cleaved RNA-based masking construct binds to the first antibody and the second antibody. A method according to paragraphs 72 or 73, which binds to an antibody.
75. A method of detecting a virus, comprising:
obtaining a sample from a subject, wherein said sample is urine, serum, blood, or saliva;
amplifying the sample RNA;
mixing said sample with an effector protein, one or more guide RNAs designed to bind to a corresponding virus-specific target molecule, and an RNA-based masking construct;
activating said RNA effector protein by binding said one or more guide RNAs to said one or more virus-specific target molecules, wherein activation of said CRISPR effector protein is detectable said RNA-based masking construct is modified such that a positive signal is produced); and detecting said signal, wherein said detection of said signal indicates said virus is present;
A method, wherein the method does not include the step of extracting RNA from the sample.
76. 76. The method of paragraph 75, wherein said amplifying step is for a duration selected from the group consisting of 2 hours, 1 hour, 30 minutes, 20 minutes, and 10 minutes.
77. 76. The method of paragraph 75, wherein said detecting step is for a duration selected from the group consisting of 3 hours, 2 hours, 1 hour, 30 minutes, 20 minutes, and 10 minutes.
78. 76. The method of paragraph 75, wherein the volume of sample required for detection is between 100 μl and 1 μl.
79. 76. The method of paragraph 75, wherein said virus is Zika virus.
80. 76. The method of paragraph 75, wherein said sample comprises two or more viruses, and wherein said two or more viruses are distinguished.
81. 76. The method of paragraph 75, wherein said RNA-based masking construct comprises.
[Example]
Example 1 General test protocol

There are two ways to perform the C2c2 diagnostic test for DNA and RNA. This test protocol may also be used with protein detection variants after delivery of detection aptamers. The first method is a two-step reaction with separate amplification and C2c2 detection. The second method combines everything in one reaction and is called a two-step reaction. Importantly, however, high concentration samples may not need to be amplified. It is an advantage to have a separate C2c2 test protocol that does not incorporate amplification.

The reaction buffer is 40 mM Tris-HCl, 60 mM NaCl, pH: 7.3.

The reaction is carried out at 37° C. for 20 minutes to 3 hours. Read at Excitation: 485 nm/20 nm, Emission: 528 nm/20 nm. A single-molecule sensitive signal may be detected after 20 minutes from the beginning, but of course the longer the reaction time, the higher the sensitivity.

Two step reaction:

Mix the reaction to resuspend two to three tubes of the freeze-dried enzyme mixture. 5 μL of 280 mM MgAc is added to this mixture to initiate the reaction. React for 10-20 minutes. Each reaction is 20 μL, which is sufficient for up to 5 reactions.

The reaction buffer is 40 mM Tris-HCl, 60 mM NaCl, pH: 7.3.

Do this for 20 minutes to 3 hours. The minimum detection time for single-molecule sensitivity studies is about 20 minutes. Sensitivity can be increased by simply reacting for a long time.

The NEB kit referred to is the HighScribe T7 High Yield kit. Use 1.5x concentration for resuspending buffer. Three tubes of freeze-dried substrate are resuspended in 59 μL of buffer and used in the above mixture. Each reaction is 20 μL, which is sufficient for 5 reactions. Single-molecule sensitivity was observed in 30 to 40 minutes in this reaction solution.

Example 2 C2C2 from Leptotorichia weedii Mediates Highly Sensitive and Specific Detection of DNA and RNA

Fast, low-cost, highly sensitive nucleic acid detection may aid in pathogen detection, genotyping, and disease surveillance in the medical setting. The RNA-guided RNA-targeted CRISPR effector Casl3a (formerly known as C2c2) arbitrarily exerts RNase activity (a 'secondary effect') upon target recognition. This secondary effect of Cas13a is combined with isothermal amplification to establish CRISPR-based diagnostics (CRISPR-Dx), providing rapid detection of DNA or RNA with attomole sensitivity and single-base mismatch specificity. Detect specific strains of Zika virus and Dengue virus using this Cas13a-based molecular detection platform SHERLOCK (Specific High Sensitivity Enzymatic Reporter UnLOCKing) to distinguish pathogenic bacteria, genotype human DNA identify cell-free tumor DNA mutations. Additionally, the SHERLOCK reaction reagents may be lyophilized for long-term storage without relying on a cold chain, and may be easily reconstituted on a paper surface for field applications.

The ability to rapidly detect nucleic acids with high sensitivity and single base specificity on a portable platform may aid in disease diagnosis and surveillance, epidemiological work and general laboratory work. Methods to detect nucleic acids exist (1-6), but they compromise between sensitivity, specificity, simplicity, cost, and speed. Clustered Short Repeated Palindromic (CRISPR) and CRISPR-Associated (CRISPR-Cas) Adaptive Immune Systems Contain Programmable Endonucleases that May be Used to Succeed in CRISPR-based Diagnostics (CRISPR-Dx) . While some Cas enzymes target DNA (7, 8), single effector RNA-guided RNases such as Cas13a (formerly known as C2c2) (8) target CRISPR RNA (crRNA) (9-11). may provide a platform for specific RNA sensing by being reprogrammed in. Upon recognition of an RNA target, activated Cas13a engages in 'collateral' cleavage of nearby non-target RNA ( 10) Via this crRNA-programmed secondary cleavage activity, Cas13a either induces programmed cell death in vivo (10) or by non-specific degradation of labeled RNA in vitro (10, 12) Capable of detecting the presence of specific RNAs, where attomolar sensitivity based on nucleic acid amplification and 3Casl3a-mediated secondary cleavage of commercial reporter RNAs (12) allows for real-time detection of targets (Fig. 17) describes the in vitro nucleic acid detection platform SHERLOCK (Specific High Sensitivity Enzymatic Reporter UnLOCKing).

Method
Cloning of the C2c2 locus and protein expression

As a bacterial in vivo efficacy assay, the C2c2 proteins from Leptotrichia weidii F0279 and Leptotrichia shauii were ordered as codon-optimized genes for mammalian expression (Genscript, Jiangsu, China), targeting β-lactamase. , or into the pACYC184 backbone with the corresponding direct repeats flanked by either non-targeting spacers. Spacer expression was driven by the J23119 promoter.

To purify the protein, the mammalian codon-optimized C2c2 protein was cloned into a protein purification-like bacterial expression vector (6x His/Twin Strep SUMO, pET-based expression vector kindly provided by Ilya Finkelstein).

Bacterial in vivo C2c2 efficiency assay

LwC2c2 and LshC2c2 bioefficiency plasmids and the β-lactamase plasmid described above (Abudayyeh 2016) were co-transformed into NovaBlue Singles competent cells (Millipore) at 90 ng and 25 ng, respectively. After transformation, cell dilutions were added to ampicillin and chloramphenicol LB agar plates and incubated overnight at 37°C. Colonies were counted the next day.

Preparation of nucleic acid targets and crRNA

Nucleic acid targets were PCR amplified with KAPA Hifi Hot Start (Kapa Biosystems), gel extracted and purified using the MinElute gel extraction kit (Qiagen). Purified dsDNA using the HiScribe T7 Quick High Yield RNA Synthesis Kit (New England Biolabs) was incubated with T7 polymerase overnight at 30° C. and RNA was purified with the MEGAclear Transcription Clean-up Kit (Thermo Fisher).

For preparation of crRNA, constructs with attached T7 promoter sequences were ordered as DNA (Integrated DNA Technologies). The crRNA DNA was annealed to a short T7 primer (final concentration: 10 uM) and incubated overnight at 37°C with T7 polymerase using the HiScribe T7 Quick High Yield RNA Synthesis Kit (New England Biolabs). The crRNA was purified using RNAXP wash beads (Beckman Coulter) at 2x beads to reaction volume and supplemented with 1.8x isopropyl alcohol (Sigma).

NASBA isothermal amplification

[Pardee 2016] provides details of the NASBA reaction. For a total reaction volume of 20 μL, 6.7 μL reaction buffer (Life Sciences, NECB-24), 3.3 μL nucleotide mix (Life Sciences, NECN-24), 0.5 μL nuclease-free water, 0.4 μL of 12.5 M NASBA primer, 0.1 uL of RNase inhibitor (Roche, 03335402001), and 4 μL of RNA amplification product (water for negative control) were combined at 4°C and incubated at 65°C. Incubate for 2 min, 41° C. for 10 min. 5 μL of Enzyme Mix (Life Sciences, NEC-1-24) was then added to each reaction and the reaction mixtures were incubated at 41° C. for 2 hours. The NASBA primers used were 5'-AATTCTAATACGACTCACTATAGGGGGATCCTCTAGAAATATGGATT-3' (SEQ ID NO: 16) and 5'-CTCGTATGTTGTGTGGAATTGT-3' (SEQ ID NO: 17). The underlined portion indicates the T7 promoter sequence.

recombinase polymerase amplification

Using NCBI Primer Blast (Ye et al., BMC Bioinformaics 13, 134 (2012)), the size of the amplified product (100-140 nt), the melting temperature of the primer (54°C-67°C), and the size of the primer (30 Primers for RPA were designed using the default parameters, except for ~35 nt) Primers were then ordered as DNA (Integrated DNA Technologies).

RPA and RT-RPA reaction runs were performed as directed in TwistAmp® Basic or TwistAmp® BasicRT (TwistDx), respectively, except that 280 mM MgAc was added prior to the input template. rice field. Reactions were carried out at 37° C. for 2 hours on 1 uL input unless otherwise noted.

Purification of LwC2c2 protein

The C2c2 bacterial expression vector was transformed into Rosetta®2(DE3) pLysS Singles competent cells (Millipore). A 16 mL starter culture was added to Terrific Broth 4 growth medium (12 g/L tryptone, 24 g/L yeast extract, 9.4 g/L _K2HPO , 2.2 g/L _KH2PO4 , Sigma) _. (TB) and used to inoculate 4 L of TB. The TB was incubated at 37° C. and 300 RPM until the absorbance OD600 was 0.6. At this time, protein expression was induced by supplementing with IPTG (Sigma) to a final concentration of 500 uM. Cells were chilled to 18° C. for 16 hours for protein expression. Cells were then centrifuged at 5200g for 15 minutes at 4°C. Cell pellets were harvested and stored at -80°C for later purification.

All subsequent steps of protein purification were performed at 4°C. Cell pellets were disrupted in lysis buffer (20 mM Tris-HCl, 500 mM NaCl, 1 mM DTT, pH: 8.0) supplemented with protease inhibitors (Complete Ultra EDTA-free tablets), lysozyme, and benzonase. and sonicated (Sonifier 450, Branson, Danbury, Conn.) at 100 amplitude for 1 sec, 2 sec off for a total sonication time of 10 min. The lysate was washed by centrifugation at 10,000 g for 1 hour at 4° C. and the supernatant filtered through a Stericup 0.22 micron filter (EMD Millipore). The filtered supernatant was added to StrepTactin Sepharose (GE) and incubated with rotation for 1 hour. The protein-bound StrepTactin resin was then washed three times in lysis buffer. The resin was added to SUMO digestion buffer (30 mM Tris-HCl, 500 mM NaCl, 1 mM DTT, 0.15% Igepal (NP-40), pH: 8.0) with 250 units of SUMO protease (ThermoFisher). Resuspend and incubate overnight at 4°C with rotation. Digestion was confirmed by SDS-PAGE and Coomassie blue staining and the protein eluate was isolated by spinning down the resin. Proteins were loaded via fast protein liquid chromatography (FPLC) (AKTA PURE, GE Healthcare Life Sciences) onto a 5 mL HiTrap SP HP cation exchange column (GE Healthcare Life Sciences) and analyzed from 130 mM to 2 M. Elution was performed with a salt gradient of NaCl in elution buffer (20 mM Tris-HCl, 1 mM DTT, 5% glycerol, pH: 8.0). Fractions obtained by SDS-PAGE were tested for the presence of LwC2c2. Fractions containing protein were pooled and concentrated to 1 mL in S200 buffer (10 mM HEPES, 1 M NaCl, 5 mM MgCl ₂ , 2 mM DTT, pH: 7.0) with a centrifugal filter device. The concentrated protein was loaded onto a gel filtration column (Superdex® 200 Increase 10/300 GL, GE Healthcare Life Sciences) by FPLC. Fractions obtained from gel filtration were analyzed by SDS-PAGE and fractions containing LwC2c2 were pooled and buffered with storage buffer (600 mM NaCl, 50 mM Tris-HCl (pH: 7.5), 5 % glycerol, 2 mM DTT) and stored frozen at -80°C.

Secondary detection of LwC2c2

45 nM purified LwC2c2 _, 22.5 nM crRNA, 125 nM substrate reporter (Thermo Detection assays were performed with Scientific RNase Alert v2), 2 μL mouse RNase inhibitor, 100 ng background total RNA, and varying amounts of input nucleic acid target. If the input was amplified DNA containing a T7 promoter from an RPA reaction, the C2c2 reaction described above was modified to contain 1 mM ATP, 1 mM GTP, 1 mM UTP, 1 mM CTP, and 0.6 μL T7 polymerase mix ( NEB) were included. Reactions were allowed to proceed for 1-3 hours (unless otherwise noted) at 37° C. with fluorescence power measured every 5 minutes in a fluorescence plate reader (BioTek).

A one-pot reaction combining RPA-DNA amplification, conversion of DNA to RNA by T7 polymerase, and C2c2 detection was performed by incorporating the reaction conditions described above into the RPA amplification mixture. Briefly, a 50 μL one-pot assay consisted of 0.48 μM forward primer, 0.48 μM reverse primer, 1× RPA rehydration buffer, various amounts of DNA input, 45 nM LwC2c2 recombinant protein, 22.5 nM crRNA, 250 ng background total RNA, 200 nM substrate reporter (RNase alert v2), 4 uL RNase inhibitor, 2 mM ATP, 2 mM GTP, 2 mM UTP, 2 mM CTP, 1 μL It consisted of T7 polymerase mix, 5 mM MgCl ₂ , and 14 mM MgAc.

Quantitative PCR (qPCR) analysis with TaqMan probes

ＳＹＢＲグリーンIIを用いたリアルタイムＲＰＡ To compare the SHERLOCK quantification method with other established methods, quantitative PCR of serial dilutions of ssDNA1 was performed. A TaqMan probe and primer set (sequence below) was designed against ssDNA1 and manufactured at IDT. Assays were performed using TaqManFast Advanced Master Mix (ThermoFisher) and measured on a Roche LightCycler 480.

Real-time RPA using SYBR Green II

To compare the SHERLOCK quantification method with other established methods, serial dilutions of ssDNA1 were subjected to RPA. To quantify DNA accumulation in real time, 1x SYBR Green II (ThermoFisher) was added to the typical RPA reaction mixture described above. SYBR Green II provides a fluorescent signal that correlates with the amount of nucleic acid. Reactions were allowed to proceed for 1 hour at 37° C. with fluorescence power being measured every 5 minutes in a fluorescence plate reader (BioTek).

Lentivirus preparation and processing

Lentiviruses were prepared and processed based on previously known methods. Briefly, 10 μg of _pSB700 derivatives containing Zika or Dengue RNA fragments, 7.5 μg of psPAX2, and 2.5 μg of pMD2. G was transfected into HEK293FT cells (Life Technologies, R7007). The medium was changed after 28 hours to supplement DMEM with 10% FBS, 1% penicillin-streptomycin, and 4 mM GlutaMAX (ThermoFisher Scientific) and the supernatant was filtered using a 0.45 μm syringe filter. Lentivirus was purified from the supernatant and prepared using the ViralBind Lentivirus Purification Kit (Cell Biolabs, VPK-104) and Lenti-X Concentrator (Clontech, 631231). Viral concentrations were quantified using the QuickTiter Lentiviral Kit (Cell Biolabs, VPK-112). Virus samples were added to 7% human serum (Sigma, H4522) and heated to 95°C for 2 minutes and used as input to RPA.

Isolation and cDNA purification of Zika human serum samples

Suspected Zika-positive human serum or urine samples were inactivated with AVL buffer (Qiagen) and RNA was isolated with the QIAamp Viral RNA Mini Kit (Qiagen). Isolated RNA was converted to cDNA by mixing random primers, dNTPs, and sample RNA and heat denatured at 70° C. for 7 minutes. The denatured RNA was then incubated at 22-25°C for 10 min, 50°C for 45 min, 55°C for 15 min, and 80°C for 10 min and reverse transcribed with Superscript III (Invitrogen). The cDNA was then incubated with RNase H (New England Biolabs) for 20 minutes at 37°C to destroy the RNA in the RNA:cDNA hybrids.

Genomic DNA extraction from human saliva

2 mL of saliva was collected from the volunteers. Participants were restricted from eating or drinking for 30 minutes prior to collection. Samples were then processed using the QIAamp® DNA Blood Mini Kit (Qiagen) as recommended in the kit's protocol. For boiled saliva samples, 400 μL of phosphate buffered saline (Sigma) was added to 100 μL of collaborators' saliva and centrifuged at 1800 g for 5 minutes. The supernatant was decanted and the pellet was resuspended in phosphate buffered saline with 0.2% Triton X-100 (Sigma) before incubating at 95°C for 5 minutes. 1 μL of sample was used as direct input to the RPA reaction.

Freeze-drying and placing on paper

Glass fiber filters (Whatman paper, 1827-021) were autoclaved for 90 minutes (Consolidated Stills and Sterilizers, MKII) and blocked overnight with 5% nuclease-free BSA (EMD Millipore, 126609-10GM). After washing the paper once with nuclease-free water (Life technologies, AM9932), it was incubated with 4% RNAsecure™ (Life technologies, AM7006) at 60°C for 20 minutes and washed three more times with nuclease-free water. . The treated papers were dried at 80° C. for 20 minutes on a hot plate (Cole-Parmer, IKA C-Mag HS7) before use. Discs (2 mm) were loaded with 1.8 μL of the C2c2 reaction mixture as indicated above and the discs were placed in a black clear bottom 384-well plate (Corning, 3544). For freeze-drying studies, plates containing reaction mixture discs were flash-frozen in liquid nitrogen and freeze-dried overnight as described by Pardee et al (2). RPA samples were diluted 1:10 in nuclease-free water and 1.8 μL of the mixture was loaded onto paper discs and incubated at 37° C. using a plate reader (BioTek Neo).

Extraction of bacterial genomic DNA

For experiments involving carbapenem-resistant Enterobacteriaceae (CRE) detection, bacterial cultures were grown in lysogeny medium (LB) to mid-log phase, pelleted and analyzed with the appropriate Qiagen DNeasy Blood and Tissue Kit. gDNA extraction and purification were performed using the manufacturer's test protocol for either Gram-negative or Gram-positive bacteria as the material. The gDNA was quantified by Quant-It dsDNA assay on Qubit fluorometer and its quality was assessed by absorbance spectrum from 200-300 nm on Nanodrop spectrophotometer.

In experiments distinguishing between E. coli and P. aeruginosa, bacterial cultures were grown to early stationary phase in Luria-Bertani (LB) broth. A portable PureLyse bacterial gDNA extraction kit (Claremont BioSolutio) was used to process 1.0 mL of E. coli and Pseudomonas aeruginosa. 1× binding buffer was added to the bacterial culture before passing through a battery-powered lysis cartridge for 3 minutes. An aqueous solution of 0.5x binding buffer was used as a wash before eluting with 150 μL of water.

Digital droplet PCR quantitation

Digital droplet PCR (ddPCR) was performed to confirm the concentrations of the ssDNA1 and ssRNA1 standard dilutions used in FIG. 1C. For DNA quantification, droplets were made using ddPCR supermix (no dUTP) for probes in a PrimeTime qPCR probe/primer assay designed to target the ssDNA1 sequence. For RNA quantification, droplets were generated using a 1-step RT-ddPCR kit for probes in a PrimeTime quantitative PCR probe/primer assay designed to target the ssRNA1 sequence. In both cases a QX200 droplet generator (BioRad) was used to generate droplets and transfer them to PCR. Droplet-based amplification was performed on a thermal cycler as described in the kit's protocol and then read on a QX200 droplet reader to determine nucleic acid concentration.

Synthetic standards for human genotyping

To generate a basis for accurately genotyping human samples, primers were designed around the SNP target to amplify a region of approximately 200 bp from human genomic DNA representing each of the two homozygous genotypes. Heterozygous controls were then mixed at a 1:1 ratio with homozygous controls. Cholera standards were then diluted to an equivalent genomic concentration (approximately 0.56 fg/μL) and used as input for SHERLOCK along with actual human samples.

Detection of tumor variant cell-free DNA (cfDNA)

Mocks of cfDNA standards that mimic real patient cfDNA samples were purchased from a commercial vendor (Horizon Discovery Group). These standards were prepared as 4 allelic fractions (100% WT and 0.1% mutant, 1% mutant and 5% mutant) for both BRAF V600E and EGFR L858R mutants. was done. 3 μL of these standards were provided as input to the SHERLOCK.

Analysis of fluorescence data

In order to calculate fluorescence data with background noise removed, the initial fluorescence of the sample was reduced to allow comparison under different conditions. Fluorescence in background conditions (either no input or no crRNA conditions) was subtracted from the samples to generate background noise-removed fluorescence.

ここで、Ａ_ｉおよびＢ_ｉはそれぞれ、所与の個体についてアレルＡまたはアレルＢを感知するｃｒＲＮＡのｉ個の技術的に同じ試料に対するＳＨＥＲＬＯＣＫ強度値を指す。典型的にはｃｒＲＮＡにつき４つの技術的に同じ試料があるので、ｍおよびｎは４と等しく、分母は所与のＳＮＰ座位および個体に対してcrRNA SHERLOCK強度値の８個すべての合計に等しい。２個のｃｒＲＮＡがあるので、１つの個体に対するこれらｃｒＲＮＡのそれぞれのｃｒＲＮＡ比平均は常に２である。従って、ホモ接合性の理想的な場合では、陽性アレルｃｒＲＮＡに関する平均ｃｒＲＮＡ比は２であり、陰性アレルｃｒＲＮＡに関する平均ｃｒＲＮＡ比はゼロである。ヘテロ接合性の理想的な場合では、２つのｃｒＲＮＡのそれぞれの平均ｃｒＲＮＡ比は１である。

ＬｗＣａｓ１３ａ切断要件の特徴付け Guide ratios for SNP or lineage discrimination were calculated by dividing each guide by the total guide value to adjust for overall diversity between samples. The crRNA ratio for SNP or lineage discrimination was calculated as follows to adjust for overall diversity between samples.

where A _i and B _i respectively refer to the SHERLOCK intensity values for i technically identical samples of crRNA sensing allele A or allele B for a given individual. Since there are typically 4 technically identical samples per crRNA, m and n equal 4 and the denominator equals the sum of all 8 crRNA SHERLOCK intensity values for a given SNP locus and individual. Since there are two crRNAs, the average crRNA ratio for each of these crRNAs for one individual is always two. Thus, in the homozygous ideal case, the average crRNA ratio for positive allele crRNA is 2 and the average crRNA ratio for negative allele crRNA is zero. In the ideal case of heterozygosity, the average crRNA ratio for each of the two crRNAs is one.

Characterization of LwCas13a cleavage requirements

Protospacer flanking sites (PFS) are specific motifs located near target sites that require robust ribonuclease activity by Casl3a. The PFS is located at the 3' end of the target site and was previously characterized by our group as H (rather than G) for LshCasl3a (1). This motif is similar to the protospacer-adjacent motif (PAM), but functionally different in terms of sequence restriction for DNA-targeted class 2 systems. This is because it is not involved in preventing self-targeting of the CRISPR loci in the endogenous system. Further structural studies of Casl3a will elucidate the importance of PFS for Casl3a:crRNA target complex formation and cleavage activity.

Ability to purify recombinant LwCasl3a protein from E. coli (FIGS. 2D-2E) and cleave 173 nt ssRNAs with each potential protospacer flanking site (PFS) nucleotide (A, U, C, or G). was assayed (Fig. 2F). Like LshCasl3a, LwCasl3a can robustly cleave targets with a PFS of A, U, or C, but has less activity on ssRNAs with a PFS of G. Although we observed weak activity against ssRNA1 with a PFS of G, we still observe robust detection for two targets with a PFS motif of G (Table 3; rs601338 crRNA and Zika target crRNA2). In each situation, PFS of H may not be necessary, and in many cases PFS of G appears to achieve stronger cleavage or secondary activity.

Discussion of Recombinase Polymerase Amplification (RPA) and Other Isothermal Amplification Methods

Recombinase polymerase amplification (RPA) is an isothermal amplification technique that consists of three major enzymes: recombinase, single-stranded DNA binding protein (SSB), and strand displacement polymerase. Since all these enzymes work at a constant temperature around 37°C, RPA overcomes many technical difficulties present in other amplification methods, especially the polymerase chain reaction (PCR), by eliminating the need for temperature regulation. are doing. In RPA, an enzymatic approach driven by DNA replication and repair in vivo replaces temperature cycling for global melting of double-stranded templates and annealing of primers. The recombinase-primer complex scans the double-stranded DNA to facilitate strand exchange at complementary sites. Strand exchange is stabilized by SSB, allowing primers to remain bound. Spontaneous degradation of the recombinase occurs in the ADP-bound state, allowing strand-displacing polymerases to penetrate and extend primers and amplify them without complex equipment that is not available in clinical and field settings. This process can be cycled repeatedly over a temperature range of 37-42° C. to effect exponential amplification of DNA. The original published formulation used Bacillus subtilis Pol I (Bsu) as the strand-displacement polymerase, T4 uvsX as the recombinase, and T4 gp32 as the single-stranded DNA binding protein (2), but was used in this study. It is unclear what ingredients are included in the current formulation marketed by TwistDx.

Also, RPA has some limitations.
1) Casl3a detection is quantitative (Fig. 15), but real-time RPA quantification can be difficult as the recombinase saturates quickly once it has used all available ATP. Real-time PCR is quantitative because the amplification can be cycled, but RPA does not have mechanisms to tightly control the amplification rate. Any adjustment may be made to reduce the rate of amplification, such as, for example, reducing the concentration of available magnesium or primers, lowering the reaction temperature, or designing less efficient primers. We have seen some examples of quantitative SHERLOCK such as Figures 31, 32 and 52, but this is not always the case and is template dependent.
2) RPA efficiency can be sensitive to primer design. Manufacturers typically design long primers to ensure efficient recombinase binding at average GC content (40-60%) and to find very sensitive primer pairs. It is recommended to screen up to 100 primer pairs. We found that for SHERLOCK, only two primer pairs had to be designed to achieve an attomole test with single-molecule sensitivity. This robustness is likely due to further amplification of the signal by constitutively active Casl3a secondary activity that offsets any inefficiencies in amplification of the amplicon. This quality is particularly important for the identification of bacterial pathogens in FIG. Since RPA does not involve a melting step, there have been various problems in amplifying highly structured regions such as the 16S rRNA gene sites of bacterial genomes. Thus, primer secondary structure becomes a problem, limiting amplification efficiency and sensitivity. The embodiments disclosed herein appear to be successful for further signal amplification from Casl3a despite these RPA-specific problems.
3) The length of amplified sequences should be short (100-200 bp) for efficient RPA. For most applications this is probably not a significant problem but perhaps even an advantage (eg cfDNA detection where the average fragment size is 160 bp). Long amplicon lengths can be important, for example, when universal primers are desired for bacterial detection and when the SNPs that discriminate are spread over a large region.

The modularity of SHERLOCK allows any amplification technique, even non-isothermal methods, to be used prior to T7 transcription and Casl3a detection. This modularity is made possible by the compatibility of the T7 and Casl3a steps in one reaction, allowing detection to be performed on any amplified DNA input with a T7 promoter. Prior to using RPA, we attempted nucleic acid sequence-based amplification (NASBA) (3, 4) in our detection assay (Fig. 10). However, NASBA did not significantly enhance the sensitivity of Casl3a (Figures 11 and 53). Other amplification techniques that may be used prior to detection include PCR, loop-mediated isothermal amplification (LAMP) (5), strand displacement amplification (SDA) (6), helicase dependent amplification (HDA) (7), and nicking. Enzymatic amplification reaction (NEAR) (8). By being interchangeable with any isothermal technique, SHERLOCK can overcome the specific limitations of any one amplification technique.

Discordance design by genetic engineering

We have previously shown that two or more mismatches in the target:crRNA duplex reduce LshCas13a target cleavage, whereas one mismatch is relatively unaffected, demonstrating that LwCas13a sideways Subsequent cuts confirmed such observations (Fig. 36A). We maintained secondary cleavage of the target because there was only one mismatch, but introduced additional mutations in the crRNA spacer sequence for secondary cleavage against targets with additional mismatches (two mismatches total). is assumed to destabilize To test the possibility of genetically enhanced specificity, we designed multiple crRNAs targeting ssRNA1 and optimized targeted secondary cleavage, including discrepancies across the length of the crRNA. , minimized secondary cleavage of targets that differed by one mismatch (Fig. 36A). Although these mismatches did not reduce secondary cleavage of ssRNA1, we observed that the signal for the target containing the additional mismatch (ssRNA2) was significantly reduced. The crRNAs designed to best discriminate between ssRNA1 and ssRNA2 contained a synthetic mismatch close to that of ssRNA2, forming a “(transcription) bubble” or distortion in the actual hybridized RNA. The loss of sensitivity caused by cooperation between synthetic mismatches and additional mismatches present in the target (i.e., double mismatches) is consistent with the sensitivity of LshCasl3a and LwCasl3a to consecutive or adjacent double mismatches, discriminating by a single nucleotide. provides the basis for the rational design of enabling crRNAs (Fig. 36B).

In detecting mismatches in ZIKV and DENV strains, our full-length crRNA contained two mismatches (FIGS. 37A, 37B). Due to the large sequence differences between the strains, we were unable to find a 28nt contiguous interval with only a single nucleotide difference between the two genomes. However, we expected the shorter crRNAs to be functional and designed shorter 23nt crRNAs against the two ZIKV strain targets containing one synthetic mismatch in the spacer sequence and only one mismatch in the target sequence. bottom. These crRNAs can distinguish between African and American strains of ZIKV (Fig. 36C). Subsequent testing of 23-nt and 20-nt crRNAs showed that shorter spacer lengths decreased activity but maintained or enhanced the ability to discriminate between single mismatches (FIGS. 57A-57G). To better understand how synthetic discrepancies are introduced to facilitate discrimination of single-nucleotide mutations, three different spacer lengths, 28 nt, 23 nt, and 20 nt, were used across the first seven positions of the spacer. Mismatches by synthesis were tiled (Fig. 57A). LwCasl3a shows greatest specificity for targets with mutations at the third position when the synthetic mismatch is at position 5 of the spacer, with lower levels of target activity but specificity at shorter spacer lengths. is improved (FIGS. 57B-57G). We also staggered the targeted mutations across positions 3-6 to tile the synthetic mismatch with spacers around the mutations (FIG. 58).

Genotyping by SHERLOCK using synthetic criteria

Evaluation of synthetic standards generated from PCR amplification of SNP loci can accurately identify genotypes (FIGS. 60A, 60B). By calculating all the comparisons of the SHERLOCK results for the individual's samples and the synthetic standards (analysis of variance), it is possible to genotype each individual by finding the synthetic standards that are most similar to the SHERLOCK detection strength (Fig. 60C, FIG. 60D). This SHERLOCK genotyping method is generalizable to any SNP locus (Fig. 60E).

SHERLOCK is an affordable and adaptable CRISPR-Dx platform

The cost analysis of SHERLOCK shows that the DNA template for synthesizing crRNA, the primers used for RPA, common buffers ( _MgCl2 , Tris-HCl, glycerin, NaCl, DTT), glass microfiber filters, and RNAsecure reagents are minor. Reagents determined to be were omitted. For the DNA template, Ultramer Synthesis from IDT provides materials for 40 in vitro transcription reactions (each sufficient to run about 10,000 reactions) for about $70 and crRNA synthesis. A small amount is added to the cost of For RPA primers, 25 nmoles of IDT synthesis of 30 nt DNA primers can be purchased for about $10 and provide material suitable for 5000 SHERLOCK reactions. Glass microfiber paper is available at 0.50/sheet, sufficient for several hundred SHERLOCK reactions. The cost of 4% RNAsecure reagent is $7.20/mL, sufficient for 500 tests.

All experiments also used 384-well plates at a cost of $0.036/reaction (Corning 3544), except for paper assays. Due to its small cost, it was not included in the overall cost analysis. Also, SHERLOCK-POC does not require the use of plastic containers as it is easily made on paper. The SHERLOCK readout method used herein was a plate reader equipped with either a filter set or a monochromator. As an investment, the cost of the leader was not included in the calculation. This is because the costs are expected to drop as more reactions are run on the plate reader, which is a small amount. In some cases, POC applications have used inexpensive portable alternatives such as handheld spectrophotometers (9) or portable electronic readers (4). These reduce the cost of the device to less than $200. These portable solutions are slower in speed and readability than bulkier devices, but are more widely available.

result

The assays and systems described herein may generally involve a two-step process of amplification and detection. In the first step, a nucleic acid sample, either RNA or DNA, is amplified, eg, by isothermal amplification. In the second step, the amplified DNA is transcribed into RNA and then incubated with CRISPR effectors (eg, C2c2) and crRNA programmed to detect the presence of target nucleic acid sequences. A reporter RNA labeled with a quenched fluorophore is added to the reaction to allow detection. Secondary cleavage of the reporter RNA abolishes the quenching effect of the fluorophore, allowing real-time detection of nucleic acid targets (Fig. 17A).

To achieve robust signal detection, orthologs of C2c2 were identified and evaluated from the organism Leptotorichia weedii (LwC2c2). The activity of the LwC2c2 protein was evaluated by expressing the protein with synthetic E. coli CRISPR sequences and programming it to cleave a target site within the β-lactamase mRNA. Cleavage leads to bacterial death under ampicillin selection (Fig. 2B). Fewer E. coli colonies with the LwC2c2 locus survived than the LshC2c2 locus. This indicates that the LwC2c2 orthologue has higher cleavage activity (Fig. 2C). The human codon-optimized LwC2c2 protein was then purified from E. coli (FIGS. 2D-2E) and assayed for its ability to cleave 173 nt ssRNA with different protospacer flanking site (PFS) nucleotides (FIG. 2F). LwC2c2 was able to cleave each of the four potential PFS targets. In addition, ssRNA with PFS of G had slightly lower activity.

Real-time measurements of LwC2c2 RNase secondary activity were measured using a commercially available RNA fluorescence plate reader (Fig. 17A). To determine the baseline sensitivity of LwC2c2 activity, LwC2c2 was incubated with ssRNA target 1 (ssRNA1), a crRNA complementary to a site within this ssRNA target, and an RNA sensor probe (Figure 18). This resulted in a sensitivity of approximately 50 fM (Fig. 27A). While this sensitivity is higher than other bacterial nucleic acid detection techniques (Pardee et al., 2014), it is not high enough for many diagnostic applications requiring detection performance at lower femtomoles (Barletta et al., 2014). 2004; Emmadi et al., 2011; Rissin et al., 2010; Song et al., 2013).

To increase sensitivity, an isothermal amplification step was added prior to incubation with LwC2c2. Coupling LwC2c2-mediated detection with conventional isothermal amplification methods such as nucleic acid sequence-based amplification (NASBA) (Compton, 1991; Pardee et al., 2016) improved sensitivity to some extent (Fig. 11). An alternative isothermal amplification method, recombinase polymerase amplification (RPA) (Piepenburg et al., 2006) was tested. DNA can be amplified exponentially in less than 2 hours using this method. Addition of the T7 RNA polymerase promoter to the RPA primers allows the conversion of the amplified DNA into RNA for subsequent detection by LwC2c2 (Figure 17). Thus, in certain exemplary embodiments, the assay comprises a combination of amplification by RPA, conversion of DNA to RNA by T7 RNA polymerase, and subsequent detection of RNA (by C2c2, which cuts off the fluorescence from the quenched reporter). including.

Using this exemplary method with the synthesized DNA version of ssRNA1, it was possible to achieve attomole sensitivity in the range of 1-10 molecules per reaction (FIG. 27B left). To confirm the accuracy of detection, the concentration of input DNA was quantified by digital droplet PCR to confirm that the lowest detectable target concentration (2 aM) was 1 molecule per microliter. Also, with the addition of a reverse transcription step, RPA may amplify the RNA into dsDNA form, which can achieve attomolar sensitivity with ssRNA1 (FIG. 27B, right). Similarly, RNA target concentration was verified by digital droplet PCR. To assess the feasibility of this exemplary method to serve as a POC diagnostic test, the ability of all components of RPA, T7 polymerase amplification, and LwC2c2 detection to function in one reaction was tested, resulting in a one-pot version of the assay. Attomolar sensitivity was observed (Figure 22).

Assay allows sensitive virus detection in liquids or on paper

Next, it was determined whether the assay would be useful for epidemic applications. Infectious disease applications require high sensitivity and may benefit from portable diagnostics. To test detection in a model system, lentiviruses harboring the Zika virus genome and related flavivirus dengue RNA fragments (Dejnirattisai et al., 2016) were generated and the number of virus particles was quantified (Fig. 31A). . Amounts of mock virus were detected down to 2aM. At the same time, it was also possible to clearly distinguish these surrogate viruses, including Zika and Dengue RNA fragments (Fig. 31B). Reaction components were freeze-dried to determine if the assay was compatible with freeze-drying to eliminate reliance on cold chains for distribution. When the sample was used to rehydrate the lyophilized component, 20 fM ssRNA1 was detected (Fig. 33A). Resource-poor and POC settings may benefit from paper testing due to its ease of use, and we also evaluated the activity of C2c2 detection on glass fiber paper surfaces and found that the paper-spotting C2c2 reaction was able to detect the target. It was observed that it was possible (Fig. 33B). Combining freeze-drying and paper spotting, the C2c2 detection reaction detected ssRNA1 with high sensitivity (Fig. 33C). Also, similar sensitivities were observed for LwC2c2 in solution and freeze-dried LwC2c2 for the detection of synthetic Zika virus RNA fragments. This demonstrates the robustness of freeze-dried SHERLOCK and the potential for rapid POC Zika virus diagnostics (FIGS. 33D-33E). To this end, potential POC variants in the assay were tested to determine their ability to discriminate between Zika and Dengue RNA (Fig. 31C). Although paper spotting and freeze-drying slightly reduced the absolute signal of the readout, the assay significantly detected the mimetic Zika virus at concentrations as low as 20 aM compared to detection of the mimetic virus with the dengue control sequence (Fig. 31D). .

Human Zika virus RNA levels reportedly as low as 3 x ¹⁰⁶ copies/mL (4.9 fM) in patient saliva and 7.2 x ¹⁰⁵ copies/mL (1.2 fM) in patient serum (Barzon et al., 2016; Gourinat et al., 2015; Lanciotti et al., 2008). Concentrations as low as 1.25×10 ³ copies/mL (2.1 aM) were observed from patient samples obtained. To assess whether the assay is capable of detecting Zika virus in low titer clinical isolates, viral RNA was extracted from patients, reverse transcribed, and the resulting cDNA was used as input for the assay. (Fig. 32A). Significant detection of Zikahito serum samples was observed up to a concentration of 1.25 copies/uL (2.1 aM) (Figure 32B). Furthermore, the signal from patient samples was predictive of Zika virus RNA copy number, which was used to predict viral load (Fig. 31F). To test its broader application to disease situations where nucleic acid purification is not available, we tested the detection of ssRNA1 spiked into human serum and found that the assay worked at serum levels below 2% (Fig. 33G).

Bacterial pathogen differentiation and genetic differentiation

The 16S V3 region was chosen as the initial target to determine whether the assay could be used to distinguish between bacterial pathogens. This is because the conserved flanking regions allow conserved RPA primers to be used across bacterial species, and the variable internal regions allow species differentiation. A panel of five potential target crRNAs was designed against pathogenic strains and isolated E. coli and Pseudomonas aeruginosa gDNAs (Fig. 34A). The assay was able to distinguish between E. coli and Pseudomonas aeruginosa gDNA, and showed low background signal for crRNAs from other species (FIGS. 34A, 34B).

The assay can also be used to rapidly detect and differentiate bacterial genes of interest (eg, antibiotic resistance genes). Carbapenem-resistant enterobacteria (CRE) are a major emerging public health problem (Gupta et al., 2011). The ability of the assay to detect carbapenem resistance genes and whether the test can distinguish between different carbapenem resistance genes was evaluated. Klebsiella pneumoniae was obtained from clinical isolates harboring the Klebsiella pneumoniae carbapenemase (KPC) resistance gene or the New Delhi metallobetalactamase (NDM-1) resistance gene, and crRNAs were designed to distinguish between these genes. All CREs had significant signals against bacteria lacking these resistance genes (Fig. 35A). It was also possible to significantly distinguish the resistance of the KPC and NDM-1 strains (Fig. 35B).

Single-base mismatch specificity of CRISPR RNA-guided RNase

It has been shown that certain CRISPR RNA-guided RNase orthologs (eg, LshC2c2) do not readily discriminate single-base mismatches (Abudayyeh et al., 2016). As shown herein, LwC2c2 also shares this feature (Fig. 37A). To increase the specificity of LwC2c2 cleavage, a system was developed to introduce a synthetic mismatch into the crRNA:target duplex. This system increases the overall sensitivity to mismatches and allows sensitivity to mismatches by a single base. Multiple crRNAs were designed against target 1. These crRNAs contain mismatches throughout the length of the crRNA (Fig. 37A) to optimize target cleavage and minimize cleavage of targets that differ by a single mismatch. These mismatches did not reduce the efficiency of cleavage of ssRNA target 1, but significantly reduced the signal to targets containing additional mismatches (ssRNA target 2). The designed crRNA that best discriminated between Target 1 and Target 2 contained a synthetic mismatch close to that of Target 2, actually forming a 'bubble'. Loss of sensitivity caused by coordination of synthetic mismatches and additional mismatches (i.e., double mismatches) present in the target is consistent with the sensitivity of LshC2c2 to consecutive or adjacent double mismatches (Abudayyeh et al., 2016). , provides a rationally designed version of the crRNA that allows discrimination by a single nucleotide (Fig. 37B).

Having shown that C2c2 can be engineered to recognize discrepancies by a single base, it was determined whether this engineered specificity could be used to distinguish between closely related viral pathogens. . Multiple crRNAs were designed to detect African or American strains of Zika virus (Figure 37A) and strains 1 or 3 of Dengue virus (Figure 37C). These crRNAs contained a single synthetic mismatch in the spacer sequence and formed a bubble of synthetic mismatch when bound to the target strain. However, when a synthetic mismatched spacer binds to a non-target strain, two bubbles are formed, the synthetic mismatch and the SNP mismatch. Synthetic mismatched crRNAs detected the corresponding strains with significantly greater signal than the non-target strains and were able to robustly discriminate strains (Figures 37B, 37D). Due to the significant sequence similarity between strains, we were unable to find a 28nt contiguous interval with only a single nucleotide difference in the two genomes to indicate true single nucleotide strain differentiation. However, we predicted that shorter crRNAs would be functional when present with LshC2c2 (Abudayyeh et al., 2016). Therefore, shorter 23-nt crRNAs were designed against two Zika strain targets containing a synthetic mismatch in the spacer sequence and only one mismatch in the target sequence. These crRNAs were able to discriminate between African and American strains of Zika with high sensitivity (Fig. 36C).

Rapid genotyping using DNA purified from saliva

Rapid genotyping from human saliva may be beneficial in diagnostics in emergency pharmacogenomic situations or hypotheses. To demonstrate the feasibility of the embodiments disclosed herein for genotyping, five loci were selected to be criteria-evaluated for C2c2 detection using 23andMe genotyping data as a representative criterion (Eriksson et al. ., 2010) (Fig. 38A). The five loci span a wide range of functional implications, including sensitivity to drugs such as statins or acetaminophen, norovirus susceptibility, and risk of heart disease (Table 15).

Saliva from four human subjects was collected and genomic DNA purified in less than one hour using a simple commercial kit. Four subjects had different sets of genotypes across these five loci, providing a sufficiently large sample space to evaluate the assay for genotyping. For each of these five SNP loci, RPA with appropriate primers was used to amplify the subject's genomic DNA, designed to specifically detect LwC2c2 and one of the two potential alleles. Detection was with crRNA pairs (Fig. 38B). The assay discriminated highly significantly between alleles and was specific enough to infer both homozygous and heterozygous genotypes. Since the DNA extraction test protocol was performed on saliva prior to detection, the assay was tested to be more suitable for POC genotyping by using saliva heated to 95°C for 5 minutes without any further extraction. determined whether it can be made The assay, which only heated the saliva of two patients for 5 minutes followed by amplification and C2c2 detection, was able to correctly genotype these patients (Fig. 40B).

Detection of cancerous mutations in hypoallelic fraction cfDNA

A test to determine whether the assay is sensitive enough to detect cancer mutations in circulating cell-free DNA (cfDNA), since the assay is highly specific for single-nucleotide differences in the target. devised. The cfDNA fragments represent a small proportion (0.1%-5%) of wild-type cfDNA fragments (Bettegowda et al., 2014; Newman et al., 2014; Olmedillas Lopez et al., 2016; Qin et al., 2016 ). A key challenge in the cfDNA field is to detect these mutations. This is because these mutations are typically difficult to spot given the large amount of unmutated DNA observed in the background in blood (Bettegowda et al., 2014; Newman et al. ., 2014; Qin et al., 2016). A cfDNA cancer test at POC may also be useful in routine screening for the presence of cancer, especially for patients at risk of remission.

The ability of the assay to detect mutant DNA in a wild-type background was determined by diluting dsDNA target 1 in a background of ssDNA 1 with one mutation in the crRNA target site (Figures 41A-41B). LwC2c2 was able to sense concentrations of dsDNA1 as low as 0.1% of background dsDNA within the attomolar concentration of dsDNA1. This result indicates that the LwC2c2 cleavage of the background mutant dsDNA1 is sufficiently low that target dsDNA can be robustly detected at an allelic fraction of 0.1%. At concentrations below 0.1%, background activity appears to be problematic, preventing any more significant detection of the correct target.

Since the assay was able to detect synthetic targets with allelic fractions in a clinically relevant range, it was evaluated whether the assay could detect cancer mutations in cfDNA. RPA primers for two different cancer mutations EGFR L858R and BRAF V600E were designed using commercially available cfDNA standards with allelic fractions of 5%, 1% and 0.1% to mimic actual human cfDNA samples. tested. Using a pair of crRNAs able to distinguish between mutant and wild-type alleles (Figure 38C), detection of 0.1% allele fraction was achieved for both mutant loci (Figures 39A-B).

consideration

Combining the natural properties of C2c2 with isothermal amplification and quenching fluorescent probes, the assays and systems disclosed herein are versatile and robust RNA and DNA detection methods for epidemic applications and rapid genotyping. It has been found to be suitable for a variety of rapid diagnostics, including A major advantage of the assays and systems disclosed herein is that new POC tests can be redesigned and synthesized in just a few days at a low cost of $0.6/test.

Since many human disease applications require the ability to detect single discrepancies, rational approaches have been developed to detect single discrepancies in target sequences by introducing synthetic single discrepancies into the crRNA spacer sequence. The crRNA was engineered to be highly specific for Other approaches to achieve specificity with CRISPR effectors rely on methods of selection against dozens of guide designs (Chavez et al., 2016). Using designed discordant crRNAs, discrimination of zicading virus strains that differ at a single discordant site, rapid genotyping of SNPs from human salivary gDNA, and detection of cancer mutations in cfDNA samples were confirmed. rice field.

The low cost and adaptability of the assay platform makes it suitable for further applications including: (i) general RNA/DNA quantification experience in replacement of specific quantitative PCR assays (e.g. Taqman), (ii) Rapid multiplexed RNA expression detection similar to microarrays, and (iii) other sensitive detection applications such as detection of nucleic acid contamination from other sources of food. C2c2 may also be used for transcript detection in biological settings (eg, in cells). The highly specific nature of C2c2 detection also makes it possible to follow allele-specific expression of transcripts or mutations associated with disease in living cells. Due to the wide availability of aptamers, it is also possible to combine detection of proteins by aptamers and elucidation of cryptic amplification sites for RPA, followed by C2c2 detection to sense proteins.

Nucleic Acid Detection by CRISPR-Cas13a/C2c2: Attomolar Sensitivity and Single Base Specificity

To achieve robust signal detection, Casl3a orthologues from Leptotorichia weedii (LwCasl3a) were identified. LwCasl3a exhibits higher RNA-guided RNase activity compared to Leptotorichia shaii Casl3a (LshCasl3a) (10) (see also Figure 2, 'Characterization of LwCasl3a cleavage requirements'). LwCasl3a (FIG. 18) (13) incubated with ssRNA target 1 (ssRNA1), crRNA, and reporter (quenched fluorescent RNA) showed a detection sensitivity of approximately 50 fM (FIG. 51, FIG. 15). This sensitivity is not high enough for many diagnostic applications (12, 14-16). We therefore sought to combine detection by Casl3a with different isothermal amplification steps (Figs. 10, 11, 53, 16) (17, 18). Among the methods explored, recombinase polymerase amplification (RPA) showed the highest sensitivity (18) and can be combined with transcription by T7, which converts the amplified DNA to RNA for subsequent detection by LwCasl3a (also See "Discussion on Recombinase Polymerase Amplification (RPA) and Other Isothermal Amplification Methods" above). We describe a combination of amplification by RPA, T7 RNA polymerase transcription of amplified DNA into RNA, and detection of target RNA by Casl3a secondary RNA cleavage-mediated release of a reporter signal as SHERLOCK.

First, the sensitivity of SHERLOCK for detection of RNA (when combined with reverse transcription) or DNA targets was determined. We achieved single-molecule sensitivity for both RNA and DNA as confirmed by digital droplet PCR (ddPCR) (Figures 27, 51, 54A, 54B). Attomolar sensitivity was maintained when all SHERLOCK components were combined in one reaction. This demonstrates the viability of this platform as a point of care (POC) (Fig. 54C). SHERLOCK is as sensitive as two established highly sensitive nucleic acid detection methods, ddPCR and quantitative PCR (qPCR), but RPA alone is not sensitive enough to detect low concentrations of targets. No (FIGS. 55A-55D). SHERLOCK is also less variable than ddPCR, quantitative PCR, and RPA as measured by the coefficient of variation for the same samples (FIGS. 55E-F).

We then investigated whether SHERLOCK would be effective in infectious disease applications where high sensitivity is required. Lentiviruses harboring genomic fragments of either Zika virus (ZIKV) or the related flavivirus dengue fever (DENV) were generated (19) (Fig. 31A). SHERLOCK detected virus particles down to 2aM and was able to distinguish between ZIKV and DENV (Fig. 31B). To explore the potential use of SHERLOCK in the field, first a lyophilized and then rehydrated Cas13acrRNA complex (20) was able to detect unamplified ssRNA1 at 20 fM (Fig. 33A). ), indicating that target detection was also possible on the surface of glass fiber paper (Fig. 33B). Other components of SHERLOCK are also adaptable for freeze-drying. RPA is provided at ambient temperature as a lyophilized reagent. It has also been previously shown that T7 polymerase tolerates freeze-drying (2). With a combination of freeze-drying and paper spotting, the Casl3a detection reaction detected ssRNA1 with considerable sensitivity as the aqueous reaction (Figs. 33C-33E). Paper spotting and freeze-drying slightly reduced the absolute signal of the readout, but SHERLOCK (Fig. 31C) was able to readily detect the mimic ZIKV virus at concentrations as low as 20 aM (Fig. 31D). SHERLOCK can also detect ZIKV in clinical isolates (serum, urine, or saliva) with titers as low as 2×10 ³ copies/mL (3.2 aM) (21). As confirmed by quantitative PCR (FIGS. 32F and 52B), ZIKV RNA extracted from patient serum or urine samples and reverse transcribed into cDNA (FIGS. 32E and 52A) yielded 1.25×10 ³ copies/mL ( 2.1 aM) could be detected. Moreover, the signal from patient samples was predictive of ZIKV RNA copy number, which could be used to predict viral load (Fig. 33F). To mimic sample detection without nucleic acid purification, we measured the detection of ssRNA1 spiked into human serum and found that Casl3a was able to detect RNA in reactions containing 2% serum (Fig. 33G). Other important epidemiological applications of CRISPR-dx are the identification of bacterial pathogens and the detection of specific bacterial genes. We targeted the 16S rRNA gene V3 region. In this region, the conserved flanking regions allow the use of universal RPA primers across bacterial species, and the variable internal regions allow for species differentiation. In a panel of five potential target crRNAs against gDNA isolated from different pathogenic strains and E. coli and Pseudomonas aeruginosa (Fig. 34A), SHERLOCK correctly genotyped the strains and showed low cross-reactivity. (Fig. 34B). SHERLOCK was also used to distinguish clinical isolates of Klebsiella pneumoniae with two different resistance genes Klebsiella pneumoniae carbapenemase (KPC) and New Delhi metallobetalactamase 1 (NDM-1) (22). (Fig. 56).

To increase the specificity of SHERLOCK, a synthetic mismatch was introduced into the crRNA:target duplex that allows LwCasl3a to discriminate between targets that differ by a single base mismatch (Figures 36A, 36B; Designing Discrepancies by Operation”). We designed multiple crRNAs with synthetic mismatches in the spacer sequence to detect either African or American strains of ZIKV (Fig. 37A) and strains 1 or 3 of DENV (Fig. 37C). . Synthetic mismatched crRNA detected corresponding strains with significantly higher signal than non-target strains (two-tailed Student's t-test; p<0.01), allowing robust strain discrimination based on one mismatch. (Figs. 37B, 37D, 36C). Furthermore, characterization revealed that Casl3a detection achieved maximum specificity while maintaining target sensitivity when the mutation was at spacer position 3 and the synthetic mismatch was at position 5. (Figures 57 and 58). The ability to detect single base differences has provided an opportunity to use SHERLOCK for rapid human genotyping. We selected five loci spanning a range of health-associated single nucleotide polymorphisms (SNPs) (Table 1) and used 23andMe genotyping data as a representative criterion for these SNPs for SHERLOCK detection. was evaluated (23) (Fig. 38A). Saliva was collected from four human subjects with different genotypes across the loci of interest and genomic DNA was extracted by either commercial column purification or direct heating for 5 minutes (20). SHERLOCK discriminated alleles with highly significant and sufficient specificity to infer both homozygous and heterozygous genotypes (Figs. 38B, 40, 59, 60; also above " Genotyping with SHERLOCK Using Synthetic Criteria”). Finally, it was investigated to determine whether SHERLOCK can detect rare cancer mutations in cell-free (cf) DNA fragments. This is difficult due to the high concentration of wild-type DNA present in the blood of patients (24-26). First, it was found that SHERLOCK can detect ssDNA1 at attomole concentrations diluted in the background of genomic DNA (Fig. 61). It was then found that SHERLOCK can also detect alleles containing single nucleotide polymorphisms (SNPs) at concentrations as low as 0.1% of background DNA (Figures 41A, 41B). SHERLOCK was then able to detect two different cancer mutations, EGFR L858R and BRAF V600E, in sham cfDNA samples with an allelic fraction as low as 0.1% (Figures 38, 39) (20). It has been shown.

実施例３ Ｃ２ｃ２は感染を防ぎ、リンパ球性脈絡髄膜炎（ＬＣＭＶ）の複製を低下させる The SHERLOCK platform is suitable for additional applications including: (i) general purpose RNA/DNA quantification as an alternative to specific quantitative PCR assays (e.g. Taqman), (ii) rapid multiplexed RNA expression detection, and (iii). Other sensitive detection applications, such as detection of nucleic acid contamination. Casl3a was also able to detect transcripts in a biological setting and to track allele-specific expression of transcripts and disease-associated mutations in living cells. SHERLOCK has been shown to be a versatile and robust RNA and DNA detection method suitable for rapid diagnostics, including infectious disease applications and sensitive genotyping. The SHERLOCK paper test can be reliably redesigned and synthesized in just a few days at a low cost of $0.61/test (and above, "SHERLOCK is an affordable Adaptable CRISPR-Dx Platform”). This is because almost all tested crRNAs showed high sensitivity and specificity. These qualities underscore the power of CRISPR-Dx and open new avenues for fast, robust and sensitive detection of biological molecules.

Example 3 C2c2 prevents infection and reduces replication of lymphocytic choriomeningitis (LCMV)

Guide RNAs were designed to bind to various regions of the LCMV genome, as shown in Figure 67 and as shown in Table 20 below.

293FT cells were transfected with a plasmid expressing Leptotorichia weedii (Lw) C2c2/Casl3a fused to msfGFP with a nuclear export signal and a plasmid expressing a guide RNA using Lipofetamine 2000. 293FT cells were seeded simultaneously with the addition of the lipofetamine-plasmid mixture. Twenty-four hours later, the transfected 293FT cells were infected with the LCMV Armstrong strain (multiplicity: 5, 1 hour) (viral titer determined by focus-forming unit assay on Vero cells). One hour after infection, the cells were washed with citrate buffer to destroy virus remaining in the infection medium that did not infect the cells. Forty-eight hours after infection, virus-containing supernatant was removed, diluted 1:10 in nuclease-free water, and used as input for RT-quantitative PCR with primers to LCMV GP. The results are shown in FIG.

293FT cells were seeded one day prior to LCMV infection so that infection was performed at 80-85% confluency. Twenty-four hours after seeding, 293FT cells were infected with the LCMV Armstrong strain (multiplicity: 5, 1 hour) (viral titer determined by focus-forming unit assay on Vero cells). One hour after infection, the cells were washed with citrate buffer to destroy virus remaining in the infection medium without infecting the cells. Twenty-four hours later, 293FT cells were transfected with the plasmid expressing Lw C2c2/Casl3a fused to msfGFP with a nuclear export signal and the plasmid expressing the guide RNA using Lipofetamine 2000. Forty-eight hours after infection, virus-containing supernatant was removed, diluted 1:10 in nuclease-free water, and used as input for RT-quantitative PCR with primers to LCMV GP. The results are shown in FIG.

293FT cells were transfected with either a plasmid expressing Lw C2c2/Cas13a fused to msfGFP with a nuclear export signal and one or more plasmids expressing guide RNAs using Lipofetamine 2000. bottom. 293FT cells were seeded simultaneously with the addition of the lipofetamine-plasmid mixture. Cells were transfected with 1-4 different guide RNAs. Twenty-four hours later, cells were infected with the LCMV Armstrong strain (multiplicity: 5, 1 hour) (viral titer determined by focus-forming unit assay on Vero cells). One hour after infection, the cells were washed with citrate buffer to destroy virus remaining in the infection medium that did not infect the cells. Forty-eight hours after infection, virus-containing supernatant was removed, diluted 1:10 in nuclease-free water, and used as input for RT-quantitative PCR with primers to LCMV GP. The results are shown in FIG.

As is evident from Figures 68-70, CRISPR systems designed to target viral RNA can reduce viral replication and thus viral load, especially when multiple guide RNAs are used.

Example 4 Genome-Wide Selection of LCMV for Cas13 Target Guidance

A genome-wide selection was performed to identify the most efficient guide RNAs. 283 guide RNAs were tiled across the LCMV genome every 50 nt on the coding strand (207 guides) and every 150 nt on the non-coding strand (76 guides).

LCMV selection design and methods: To perform genome-wide selection of guides that reduce LCMV replication, guides were tiled across both the S and L segments of the LCMV genome. In the coding region, 28nt guides were designed every 50nt along the coding region. In non-coding regions, guides were designed every 150 nt. LCMV has four coding regions for four proteins (GPC, NP (or dN), Z, and L) and each of these four proteins has its own noncoding region. A total of 283 guides were tested in this method. GPC: 11 guides in noncoding region, 32 guides in coding region; NP: 12 guides in noncoding region, 35 guides in coding region; Z: 4 guides in noncoding region, coding 7 guides in the region; L: 49 guides in the noncoding region, 133 guides in the coding region. The spacer sequence of each gRNA, its relative position within the LCMV genome, and the LMCV gene are shown in Table 21 below.

実施例５ ジカｃＤＮＡ、ＲＮＡ、およびウイルス粒子の検出限界の決定 For selection, HEK293FT cells were reverse transfected with a plasmid encoding Casl3a with BFP fluorescence and a plasmid encoding one guide using Lipofetamine 2000. Three control guides were also transfected, one empty vector and two non-targeting guides. Twenty-four hours after transfection, cells were infected with GFP-expressing LCMV at a multiplicity of 1 for 1 hour. Viral replication was then measured 48 hours post-infection (72 hours post-reverse transfection) as measured by GFP fluorescence. Fractions of guides that reduce viral replication are shown in Figure 71 and Table 22 below. The amount of virus reduced, as measured by the fold change in GFP fluorescence, is shown in FIG. FIG. 73 shows representative images showing GFP depletion. As is evident from Figure 74, the targeting guides are clustered along the LCMV genome.

Example 5 Determination of Detection Limits for Zika cDNA, RNA, and Viral Particles

Detection limits for Zika cDNA, RNA, and viral particles were determined using the SHERLOCK method with Zika virus-specific RPA primers and Zika virus-specific crRNA.

To detect the cDNA, the Zika virus cDNA from the virus seed stock was diluted with water or urine. Heat inactivation was performed to mimic the heat inactivation treatment of virus particles in clinical samples and to inactivate RNA present in human urine. RPA was performed for 20 minutes followed by Casl3a detection. The fluorescence intensity shown in the bar graph was measured after 1 hour (Fig. 77A).

For RNA detection, Zika virus RNA from viral seed stocks was diluted in water, urine, or urine previously inactivated with heat and RNase. TCEP/EDTA is added to heat and RNase inactivated healthy urine prior to heat treatment. This treatment demonstrates the importance of RNase inactivation to prevent RNA degradation. RT-RPA was performed for 20 minutes followed by Casl3a detection. The fluorescence intensity shown in the bar graph was measured after 1 hour (Fig. 77B).

To detect virus particles, Zika virus particles from cell culture supernatants were diluted in PBS or urine. Samples were then heat and RNase inactivated with TCEP/EDTA and heat treated for 25 min (20 min at 55°C, 5 min at 95°C). This two-step heat treatment can inactivate RNase in the urine before releasing RNA from the virus particles (Zika virus particles are stable at temperatures below 65°C). After inactivation of the RNase, a 95° C. step releases the RNA from the virus particles. RT-RPA was performed for 20 minutes followed by Casl3a detection. The fluorescence shown in the bar graph was measured after 1 hour (Fig. 77C).

Single nucleotide variants in virus samples were detected as follows. Samples were tested with both crRNAs targeting mutant sequences and crRNAs targeting wild-type sequences. Relative fluorescence was used to determine the alleles present (Fig. 78A).

Figure 78B shows the genomic locations of the three SNPs tested with the SHERLOCK method. A simplified phylogenetic tree shows the relationship between these SNPs and those that occurred during the 2015 Zika virus outbreak.

The graph shown in Figure 78C corresponds to the different SNPs that occurred during the 2015 Zika virus outbreak and where the SNPs occurred. Each bar represents a synthetic g-block with sequence corresponding to either a mutant or wild-type variant, a cDNA from a seed stock with ancestral sequence (i.e., a variant without mutation), or no input. (water). Each sample was amplified with RPA for 20 minutes. Bars represent fluorescence after 1 hour of detection reaction. Dark-shaded bars represent fluorescence measured when mutant crRNA is used in the detection reaction, light-shaded bars represent fluorescence measured when wild-type crRNA is used.

The cDNA was derived from 3 clinical samples. cDNAs (unmutated variants) from seed stocks with ancestral sequences associated with each location of the 2015 Zika outbreak were tested with mutant and wild-type crRNAs. The graph shown in Figure 78D represents the fluorescence intensity ratio of mutant cRNA and wild-type cRNA after 1 hour. A ratio greater than 1 indicates that the mutant crRNA is more fluorescent than the wild-type crRNA, thus indicating the presence of the mutant variant in the sample tested. Purple is DOMUSA SNP, orange is USA SNP and green is HND SNP.

The heat map in Figure 78E shows the log ₂ transformed ratio of the fluorescence intensities shown in Figure 78D for each sample against each of the crRNAs. Values greater than 0 indicate the presence of mutant variants.

S139N is a variant recently identified as playing a role in the microcephalic phenotype observed during the recent Zika outbreak (Yuan, L. 2017. Science). Each bar in FIG. 78F represents either the S139N variant or a synthetic g-block with sequence corresponding to the N139S variant, cDNA from seed stock with the S139N variant, or no input (water). . Each sample was amplified with RPA for 20 minutes. Bars represent fluorescence after 1 hour of detection reaction. Dark-shaded bars represent fluorescence measured when S139N-targeted crRNA was used in the detection reaction, and light-shaded bars represent fluorescence measured when N139S-targeted crRNA was used. We were able to design RPA primer guides and test them within a week of the announcement that this variant was associated with microcephaly. This underscores the speed/immediacy of the method of the present invention.

Example 6 Dengue Virus SHERLOCK Panel

A multi-serotype dengue SHERLOCK panel is shown in FIG. 79A. A set of RPA primers specific for dengue fever is used for RPA. The RPA reactions can then be divided into four reactions (with serotype-specific guides in each reaction) to distinguish between the four serotypes of dengue virus. In Figure 79B, each tick on the x-axis represents a g-block template that was used as input for the SHERLOCK reaction. Each template was amplified with a set of RPA primers, and each RPA reaction was then tested against each of the crRNAs (DENV1 crRNA, DENV2 crRNA, DENV3 crRNA, and DENV4 crRNA). RPA reactions were carried out for 20 minutes. The fluorescence intensity shown in the bar graph was measured after 3 hours. Each purple shade indicates a serotype-specific crRNA. An alternative display of this bar graph is shown in FIG. 79C as fluorescence on a log ₁₀ scale.

Example 7 SHERLOCK panel of various flaviviruses

FIG. 80A shows how the flavivirus SHERLOCK panel works. A set of RPA primers capable of amplifying four different related flaviviruses is used for RPA. The RPA reactions can then be divided into four reactions (with virus-specific guides in each reaction) to distinguish the presence of Zika virus, West Nile virus, dengue virus, and yellow fever virus. . In Figure 80B, each tick on the x-axis represents a g-block template that was used as input for the SHERLOCK reaction. Each template was amplified with a set of RPA primers and then each RPA reaction was tested against each of the crRNAs (ZIKV crRNA, WNV crRNA, DENV crRNA and YFV crRNA). RPA reactions were carried out for 20 minutes. The fluorescence shown in the bar graph was measured after 3 hours. Each color represents a virus-specific crRNA. In FIG. 80C, each tick on the x-axis represents two g-block templates that were used as inputs for the SHERLOCK reaction to mimic SHERLOCK's ability to detect co-infections. Each reaction was amplified with a set of RPA primers and then tested against each of the crRNAs (ZIKV crRNA, WNV crRNA, DENV crRNA, and YFV crRNA). RPA reactions were carried out for 20 minutes. The fluorescence shown in the bar graph was measured after 3 hours. Each color represents a virus-specific crRNA. White and gray blocks alternate, with each bar representing the fluorescence obtained from guides tested in the order of ZIKV crRNA, WNV crRNA, DENV crRNA, and YFV crRNA stored in each block. An alternative display of the measured fluorescence shown in the bar graphs of Figures 80B and 80C is shown in Figures 81A and 81B, respectively.

Example 8 Virus diagnosis by CRISPR-Cas13a

Applicants use the CRISPR-Cas13 detection platform SHERLOCK to detect Zika virus directly from urine, to distinguish between multiple pathogenic viruses, and to identify clinically relevant adaptive mutations.

Recent viral outbreaks have highlighted significant challenges in diagnosing viral infections, especially in areas remote from clinical laboratories. Viral diagnosis was particularly difficult for the 2016 ZIKV outbreak. This is partly because ZIKV is maintained at low titers in human samples and is a transient infection. Limitations of existing diagnostic techniques resulted in the first clinically confirmed cases after the virus had been circulating for many months (Metsky et al. 2017). For example, detection of nucleic acids is very sensitive and rapidly adaptable, but requires extensive sample manipulation and expensive instrumentation. In contrast, antigen and antibody tests are fast and require minimal equipment, but are less sensitive and can take months to develop. An ideal diagnosis would combine the sensitivity, specificity, and flexibility of nucleic acid diagnostics with the low cost and speed of antigen-based testing. Such diagnostics could be rapidly developed and deployed in the face of emerging viral outbreaks and would be well suited for field disease surveillance.

Here, we develop a viral diagnostic method using the Cas13-based nucleic acid detection platform SHERLOCK (Specific High Sensitivity Enzymatic Reporter UnLOCKing) (Figure 82A). The RNA-guided ribonuclease Cas13 can amplify the signal more than 1,000-fold by secondary cleavage, increasing specificity based on crRNA:target pairs. Cas13 also enables a highly adaptable viral diagnostic platform. This is because it is possible to target new viral pathogens or mutations simply by altering the crRNA sequence. Pairing Casl3a with upstream isothermal amplification using recombinase polymerase amplification (RPA) further enhances its sensitivity without the requirement for expensive instrumentation. Using the SHERLOCK platform, Applicants will develop diagnostics to detect viruses directly from bodily fluids, generate viral panels to distinguish between multiple viral species and strains, and identify clinically relevant mutations.

Applicants first examined the sensitivity of the SHERLOCK assay for ZIKV (Gootenberg et al. 2017) and determined that it has one copy (1 cp) sensitivity to ZIKV cDNA (Figure 86). Applicants evaluated the performance of SHERLOCK on a set of 40 cDNAs derived from samples from the 2016 ZIKV outbreak (Figure 82B, Figure 87). This included 37 samples from patients with ZIKV (13 plasma, 13 serum, and 11 urine samples) and 3 samples from mosquito sources. Applicants were able to detect ZIKV in cDNA from 25 of 37 clinical samples (68%) and 3 of 3 mosquito sources (100%). Applicants compared the PCR method and SHERLOCK detection, which included more amplified products, for these 40 cDNA samples. In the PCR method, ZIKV cDNA is tiled and amplified using two different sources of PCR primers containing 35 target sites (Quick et al. 2017) (Figure 82C). Applicants quantified these amplicon PCR products using the Agilent Tapestation and selected thresholds to determine the presence or absence of ZIKV (dashed red line) to maximize accuracy as measured by genomic sequence coverage. (Figure 88, see Methods for details). Of the 32 samples that were positive using at least one method, 25 were positive by both methods with 78% concordance (see Venn diagram). Both methods had the same performance even though the whole genome was tiled by amplicon PCR and the input volume of amplicon PCR (2.5 μl) was larger than SHERLOCK (1 μl). . These results demonstrate the sensitivity of SHERLOCK and its successful application to clinical samples.

Nucleic acid extraction is time consuming, requires expert knowledge, and is often not feasible in the field. Applicants have therefore developed a SHERLOCK test protocol that can amplify and detect nucleic acids from urine without extraction. Applicants used a combination of heat and chemical reduction to lyse virus particles and inactivate RNase present at 1 μg/ml in urine (Fig. 89) (Weickmann and Glitz 1982). . Applicants used this processed urine directly as input to the RPA without dilution. This method allowed detection of one copy of ZIKV cDNA diluted in urine (Fig. 83A). Dilution of ZIKV RNA in untreated urine decreased the sensitivity to 3.6 fM (1,800 cp/μl), likely due to RNase degradation (FIG. 83B). Dilution of ZIKV RNA in treated urine allowed detection with sensitivity as high as water (36 aM or 18 cp/μl, Figure 90). Naturally, ZIKV RNA is packaged into virus particles that protect the RNA from degradation. Applicants have developed a two-step thermal inertness test protocol. First, the sample is heated below the melting temperature of ZIKV particles to inactivate RNases and heated to 95° C. for 5 minutes to lyse and inactivate viral particles (FIG. 91) (Muller et al. 2016). This allowed sensitive detection of ZIKV from infectious particles at 20 aM (10 cp/μl) in less than 2 hours (Fig. 83C). To achieve a sensitivity of 6 aM (3 cp/μl) in urine, we used a 3 hour detection step for a total turnaround time of less than 4 hours (Fig. 83C, inset).

Many genetically and antigenically similar flaviviruses co-circulate within America and Africa. Applicants have therefore extended SHERLOCK by developing a diagnostic panel that detects related virus species and distinguishes between virus serotypes. Using laboratory-developed probe design algorithms, Applicants have identified ZIKV, dengue virus (DENV), West Nile virus (WNV), and yellow fever virus (YFV) can be rapidly identified. Thus, a pair of RPA primers can amplify any of the four viruses, and the species-specific crRNA can detect one or more viruses present in a given sample. (Fig. 84A). Applicants have discovered a universal flavivirus RPA primer that virus-specific crRNA is highly specific for the presence of synthetic ZIKV, DENV, WNV, and YFV DNA targets with less than 0.22% cross-reactivity. can be detected effectively (Fig. 84B, Fig. 92). This assay can also detect the presence of flaviviruses in all pairwise combinations. This demonstrates the ability of this assay to detect mock co-infections (Fig. 84C, Fig. 93). In addition to specifically detecting related viruses, Applicants designed a SHERLOCK panel to distinguish between different DENV serotypes using DENV-specific RPA primers and serotype-specific crRNAs. (Fig. 84D). Applicants were able to distinguish between DENV serotypes 1-4 with less than 3.2% cross-reactivity (Fig. 84E, Fig. 94). Thus, SHERLOCK can be extended to detect and differentiate related viruses or serotypes without the need for virus- or serotype-specific RPA primers.

SHERLOCK is uniquely prepared for the identification of field-deployable variants. Single nucleotide polymorphism (SNP) identification typically involves the use of sequencing techniques that require extensive sample processing and are difficult to deploy in the field. SHERLOCK may be used to identify SNPs with a SNP at position 3 of crRNA and a synthetic mismatch at position 5 of crRNA (Figure 85A) (Gootenberg et al. 2017). Applicants designed a SHERLOCK diagnostic for three region-specific SNPs from the 2016 ZIKV outbreak (Fig. 85B). Applicants demonstrated the performance of each of these assays on synthetic target and ancestral viral seed stocks (Figure 85C). To determine the genotype of a sample, we take the ratio of the fluorescence intensity of the originating crRNA (Fig. 85A, dark-shaded bars) and the ancestral crRNA (Fig. 85A, light-shaded bars). This ratio will be greater than 1 for samples containing SNPs and less than 1 for samples without SNPs. Applicants tested the SNP assay on cDNA samples from patients in Honduras and the Dominican Republic and a mosquito source from the United States (Fig. 85D). Applicants observed the expected fluorescence intensity ratios as shown in the bar graph (Fig. 85D) and heat map (Fig. 85E). These results emphasize the single-nucleotide specificity of SHERLOCK.

Finally, Applicants have shown that SHERLOCK can be rapidly adapted to identify emerging functional mutations. Within a week of the publication of a report (Yuan et al. 2017) describing a ZIKV point mutation in prM(S139N) that contributes to fetal microcephaly (Fig. 95), Applicants identified the nucleic acid sequence as S139N A SHERLOCK diagnostic that can distinguish between the presence and absence of mutations was successfully designed, ordered, and tested (Fig. 85F). Applicants tested an alternative crRNA design (no synthetic mismatch, SNP at position 7) that could also distinguish between the 139S and 139N alleles (Figure 96). To further demonstrate the ease with which new SHERLOCK diagnostics can be developed for clinically relevant mutations, we performed assays for the six most commonly observed drug resistance mutations in HIV reverse transcriptase. was developed in one week (Fig. 97). These developments underscore the adaptability and specificity of the SHERLOCK platform.

Applicants have identified various useful features of viral SHERLOCK diagnostics, including sensitivity, speed, ease of use, the ability to multiplex viral diagnostic panels, and the ability to genotype clinically relevant SNPs. Indicated. The short turnaround time and low requirements for sample processing will allow field testing of SHERLOCK in the near future. Also, SHERLOCK diagnostics are readily developed for a variety of viral diseases, including hemorrhagic fevers, sexually transmitted diseases, and respiratory diseases, as well as emerging viral pathogens.

Example 8 Method

Clinical Specimens/Ethics Statement. The clinical samples used in this study were collected from the Institutional Review Boards/Ethics Review Committees of la Plaza de la Salud (Santo Domingo, Dominican Republic), the Florida Department of Health (Tallahassee, FL), and the Universidad Nacional Autonoma de Honduras (Tegucigalpa, Honduras). ) from clinical studies evaluated and approved in The Institutional Review Board/Ethics Review Committee at the Massachusetts Institute of Technology (MIT) and the Office of Research Subject Projection at the Broad Institute approved the use of samples collected by the institutions indicated above.

Preparation of LwCasl3a and crRNA LwCasl3a was purified as described (Gootenberg et al. 2017). The crRNA DNA template was annealed to the T7 promoter oligonucleotide at a final concentration of 10 μM in 1× Taq reaction buffer (NEB). This involved denaturation at 95° C. for 5 minutes, followed by annealing down to 4° C. at 5° C. for 1 minute. The crRNA was transcribed in vitro using the HiScribe T7 High Yield RNA Synthesis Kit (NEB). Transcriptions were performed in volumes scaled up to 30 μl according to the manufacturer's instructions for short RNA transcripts. Reactions were incubated overnight at 37°C. Transcripts were purified using RNAClean XP beads (Beckman Coulter) at a ratio of 2x reaction volume supplemented with an additional 1.8x isopropyl alcohol.

Sample Preparation Viral RNA was extracted from 140 μl of input material using the QIAamp Viral RNA mini kit with carrier RNA (QIAGEN) according to the manufacturer's instructions. Samples were eluted in 60 μl and stored at -80°C.

For cDNA generation, 5 uL of extracted RNA was converted to single-stranded cDNA using previously published methods (Matranga et al. 2014). Briefly, RNA was reverse transcribed with SuperScript III and random hexamer primers. The RNA-DNA duplex was then digested with RNase H.

One cultured isolate ZIKV pernambuco (isolate PE243, KX197192.1) was used in ZIKV detection experiments as a positive control or ancestral sequence control. Viral RNA was removed from seed stock samples.

RNase inactivation of urine samples was performed by adding TCEP/EDTA and heating the samples. TCEP and EDTA were added to urine samples at final concentrations of 100 mM and 1 mM, respectively. Two test protocols were used: one step inactivation at 95°C for 10 minutes, or two steps inactivation at 50°C for 20 minutes followed by 95°C for 5 minutes. Inactivation was performed using a thermal cycler (Eppendorf MasterCycler) or a dry heat block.

RPA reactions and primer design RPA reactions used the Twist-Dx RT-RPA kit according to the manufacturer's instructions. Primer concentration was 480 nM. Amplification reactions involving RNA used Murine RNase inhibitor (NEB M3014L) at a final concentration of 2 units per microliter.

For ZIKV detection, RPA primers RP819/RP821 from a recent publication (Gootenberg et al. 2017) were used. The flavivirus panel used the RPA primers FLAVI-NS5fwd-1/FLAVI-NS5rev-1. The Dengue virus panel used the RPA primers DENV-3UTRfwd-1/DENV-3UTRrev-1. RPA primers DOMUSA-5249-fwd / DOMUSA-5249-rev (DOMUSA5249 SNP), USA-935-fwd / USA-935-rev (USA935 SNP), and HND-2788-fwd / for region-specific Zika SNP detection HND-2788-rev (HND2788 SNP) was used. Detection of the Zika SNP associated with microcephaly used the RPA primers ZIKV-mcep-fwd and ZIKV-mcep-rev. Detection of HIV reverse transcriptase drug resistance SNPs using RPA primers HIVRT-149F/HIVRT-348R (K65R, K103N, and V106M SNPs), and HIV-462F/HIVRT-601R (Y181C, M184V, and G190A SNPs) .

Detection reactions were performed as described above, except that 25 ng of background RNA was used instead of 100 ng of the Cas13a detection reaction and crRNA design (Gootenberg et al. 2017). This can speed up the reaction without introducing any spurious cleavage of the reporter oligonucleotide. RNase Alert v2 (Thermo) was used as a reporter unless otherwise stated. A Biotek microplate reader (Synergy H4, Neo2, and Cytation 5) was used to measure the fluorescence of the detection reactions. Fluorescence kinetics were monitored using a monochromator with 485 nm excitation, 520 nm emission and readings every 5 minutes for up to 3 hours. No significant difference in sensitivity between different machines was found.

For ZIKV detection, we used the crRNA 'Zika target crRNA2' from a recent publication (Gootenberg et al. 2017). The flavivirus panel used crRNAs ZIKV-NS5at9227 (ZIKV), DENV-NS5at9127 (DENV), WNV-NS5at9243 (WNV), and YFV-NS5at9122 (YFV). The dengue virus panel used crRNAs D1-3UTRat10457 (DENV1), D2-3UTRat10433 (DENV2), D3-3UTRat10419 (DENV3), and D4-3UTRat10366 (DENV4). For region-specific Zika SNP detection, crRNA DOMUSA-5249-Ancestral/DOMUSA-5249-derived (DOMUSA5249 SNP), USA-935-Ancestral/USA-935-derived (USA935 SNP), and HND-2788-Ancestral/HND -2788 origin (HND2788 SNP) was used. For detection of the Zika SNP associated with microcephaly, crRNA ZIKV-mcep-snp3syn5-ancestor/ZIKV-mcep-snp3syn5-derived (design shown in FIG. 85F), and crRNA ZIKV-mcep-snp7-ancestor/ZIKV -mcep-snp7 derived (design shown in Figure 96) was used. For detection of HIV reverse transcriptase drug resistance SNPs, crRNAs HIVRT-K65R-ancestor/HIVRT-K65R-derived (K65R SNP), crRNAs HIVRT-K103N-ancestor/HIVRT-K103N-derived (K103N SNP), crRNAs HIVRT-V016M- progenitor/HIVRT-V106M-derived (V106M SNP), crRNAs HIVRT-Y181C-ancestor/HIVRT-Y181C-derived (Y181C SNP), crRNAs HIVRT-M184V-ancestor/HIVRT-M184V-derived (M184V SNP), and crRNAs HIVRT-G190A-ancestor / HIVRT-G190A-derived (G190A SNP) was used.

Data Analysis Background correction was performed by subtracting fluorescence intensity values after 10 minutes (FIGS. 82-84) or 20 minutes (FIG. 85) when minimal fluorescence was observed. For both flavivirus and dengue virus panels, background-corrected fluorescence was normalized to target-specific fluorescence. Target-specific fluorescence is the background-corrected mean fluorescence of no input (water) controls with the same crRNA subtracted from the background-corrected fluorescence of a given DNA target with a given crRNA at each time point. be.

In the analysis of ZIKV samples from the 2016 pandemic (Figure 82), a threshold was used to determine the presence or absence of ZIKV. Background-subtracted fluorescence from five samples, four healthy human urine samples from one donor and one no-input water control, was used to determine the SHERLOCK fluorescence threshold. That is, for each of these five samples, we took the mean m _s and standard deviation σ _s of fluorescence over three technically identical samples. The threshold was set to the center value of {m _s +3σ _s } of 5 values. Information from the genome assembly was used to determine a threshold amplicon PCR yield. First, the amplicon PCR yield for each sample was calculated by taking the lowest concentration from each of the two amplicon PCR sources (Figure 87A). The objective is then to determine whether a particular target portion r of the genome is present in the sample (in this case the RPA amplification product that we detect with SHERLOCK). The probability Pr _s (r) that a particular target portion r is present in sample s may be estimated as the fraction of the ZIKV genome sequenced and assembled from the cDNA of sample s (the calculation of the probability across the genome is , it is preferable to simply check whether there is genomic coverage at portion r, since lack of coverage does not necessarily indicate the absence of a particular target portion r). Data for this analysis are derived from individual technically identical samples from a recent genome sequencing study of the ZIKV outbreak (Metsky et al. 2017). A plot of the amplification product PCR yield versus the fraction of genome covered is shown in FIG. 87B. The value Pr _s (r) may be used to estimate the precision and recall for each choice of threshold. In particular, an estimate of the number of samples without a particular target moiety r is the sum of Pr _s (r) for all samples. Similarly, samples P whose amplification product PCR yield exceeds a predetermined threshold are correctly labeled as having r present and estimated as the sum of Pr _s (r) in sample P. FIG. 87C shows precision and recall for each choice of threshold and F _0.5 score. The F _0.5 score is a composite metric that considers the threshold ability to correctly classify samples with the target portion of ZIKV. The amplicon PCR yield threshold is set to maximize the F _0.5 score.

For SNP identification, background-subtracted fluorescence values were calculated using ancestral target crRNA and derived target crRNA. Applicants determined the presence or absence of a SNP by taking the ratio of the background-subtracted fluorescence of the origin target crRNA to the background-subtracted fluorescence of the ancestral target crRNA. For HIV SNPs (FIG. 97), we calculated the SNP identification index. This index is a ratio obtained by dividing the fluorescence intensity ratio of the origin allele by the fluorescence intensity ratio of the ancestral allele. The SNP identification index is equal to 1 if there is no characteristic force between the two alleles, and is higher when the ratio of fluorescence intensities of the two alleles is different.

ZIKV detection experiments cDNA from PE243 seed stock was used at a stock concentration of 6.8 x ¹⁰⁴ cp/ul. cDNA was serially diluted 1:10 in ultrapure water (Life Technologies) or healthy urine (Lee Biosolutions). 4-8 μl of each sample was inactivated and 1-2 μl was used as input for the RPA reaction. Used at 2.72×10 ⁵ cp/ul of RNA in a PE243 seed stock. RNA was serially diluted in ultrapure water (Life Technologies) or healthy urine (Lee Biosolutions). 4-8 μl of each sample was inactivated and 1-2 μl was used as input for the RPA reaction.

A cultivated isolate, strain PRVABC59 (KU501215), was used for virus particle experiments. PRVABC59 was cultured in insects. Non-human primate cell lines and original stocks were purchased from ATCC (ATCC VR-1843).

Virus Panel Experiments For both flavivirus and dengue virus panels, synthetically generated DNA templates were used as inputs at a concentration of 10 ⁴ copies/μL. No input (water) controls were used as negative controls for each of the crRNAs tested. All experiments used three technically identical samples, with the MgAc concentration increased to 20 mM in the RPA reactions.

For the flavivirus panel, ZIKV template sequences were generated from (KX197192), DENV (NC_001477.1), WNV (NC_09942.1), and YFV (AY968065.1). The RPA reaction amplifies part of the NS5 of these flaviviruses.

For the Dengue virus panel, DENV1 template sequences were generated from (KM204119.1), DENV2 (KM204118.1), DENV3 (KU050695.1), DENV4 (JQ822247.1). Part of the 3' untranslated region of DENV1-4 is amplified by the RPA reaction.

SNP identification experiments. Identification of SNPs specific to regions with ancestral or derived alleles demonstrated the performance of the SNP identification assay using a synthetic template containing a 400nt fragment of the ZIKV genome. ZIKV cDNA samples from three countries (USA, Honduras, and Dominican Republic) were also used to confirm performance against mosquito sources and clinical samples. PE243 seed stock cDNA (KX197192.1) was used as an outgroup control at 300 cp/μl. A no input (water) control was also used. In experiments to identify SNPs associated with microcephaly, a synthetic template containing a 400 nt fragment of the ZIKV genome with an ancestral or derived allele was used at 10 ⁴ cp/μl and cDNA from PE243 seed stocks was used at 300 cp/μl. Using. For HIV drug resistance SNP identification experiments, a synthetic template containing a 468 nt fragment of the HIV genome with an ancestral or derived allele was used at 10 ⁴ cp/μl. Three technically identical samples were used in all SNP identification experiments.

Example 9 Programmable Cas13-Based Antiviral Therapies and Companion Diagnostics

Infectious diseases threaten our health and safety, but standard diagnostics and treatments have limited efficacy and are based on decades-old science and systems. Most epidemics go undiagnosed and untreated, and epidemics take too long to diagnose. Nucleic acid diagnostics are approved for only 11 viruses, and only 9 viral diseases can be addressed by FDA-approved antiviral therapies (De Clercq and Li, 2016). This means that we are able to diagnose and treat less than 10% of viral pathogens known to infect humans (Hulo et al., 2011). Moreover, viruses can rapidly evolve resistance to therapy, limiting the effectiveness of existing antiviral measures. There is an urgent need to develop new tools that can quickly and accurately diagnose infectious diseases anywhere in the world, identify and track known and novel infectious threats, and develop diagnostically informed antiviral treatments. be.

Applicants have recently discovered a CRISPR-Cas13 system that can be used to detect and cleave specific RNA sequences, demonstrating their potential use against epidemics (Abudayyeh et al. , 2016; Gootenberg et al., 2017). Casl3 is an RNA-guided RNA-targeted CRISPR effector that exhibits ribonuclease activity upon recognition of RNA targets such as pathogen nucleic acids. By programming the CRISPR-Casl3 system to directly target viral RNA, Applicants will be able to develop highly multiplexed antiviral therapeutics and viral diagnostics. The CRISPR-Cas13 system is therefore primed for application to RNA viruses and could be a more specific alternative to quantitative PCR diagnostics and shRNA therapeutics.

Herein, Applicants provide new methods that address the above-mentioned shortcomings of diagnosing and treating virally infected patients. Applicants will use Cas13-based systems to develop programmable therapeutics that counteract viral threats and prevent the evolution of drug resistance. Applicants also create a fast, sensitive, low-cost companion diagnostic that identifies specific pathogen sequences containing specific polymorphisms (eg, drug resistance mutations). This represents a powerful adaptive method of inhibiting viral replication and highlights the importance of Cas13 for developing new diagnostic and therapeutic applications. More broadly, similar approaches can position Casl3-based systems as new cutting-edge tools for rapidly identifying infectious agents and treating patients.

Antiviral drugs do not exist against most emerging viruses, and the available direct-acting antiviral agents (including small molecules, short interfering RNAs, and antibodies) are typically few. of highly mutable viral proteins or RNA. This is a problem. This is because RNA viruses can evolve rapidly and easily acquire resistance to existing therapeutics. Cas13-based systems offer flexibly adaptable, highly multiplexed and programmable antiviral therapeutics that target viral RNA directly or target novel viruses or emerging pandemic pathogens do. Cas13-based therapeutics may be used in combination with existing antiviral compounds against the virus when such antiviral compounds exist. This can reduce the prevalence of specific drug resistance mutations. Perhaps most importantly, once the virus develops resistance to a specific Cas13 guide RNA sequence, it is easy to switch to a different guide RNA sequence or design new guide sequences that target new mutations. Such methods prevent the widespread development of resistance to Cas13-based therapies and address a common challenge facing current antiviral therapeutics.

Current gold standard pathogen diagnostic methods are expensive, time consuming and often not sensitive enough to diagnose viral infections. Standard molecular amplification methods, such as RT-quantitative PCR, typically require nucleic acid extraction and expensive thermal cycling equipment. Immunoassays such as ELISA detect only one target, may cross-react with antigenically similar targets, and cannot be rapidly developed or updated to address new and emerging threats. A novel CRISPR-based platform (SHERLOCK) can transform the diagnosis of viral diseases with single molecule detection sensitivity and single nucleotide polymorphism specificity (Gootenberg et al., 2017). Applicants can use SHERLOCK for use as a companion diagnostic to inform Cas13-based therapies. To do so, Applicants employ a technique that uses clinical samples as direct input instead of purified nucleic acid, allowing high performance to reduce the turnaround time to less than one hour. In addition, Applicants will develop specific Cas13-based therapeutics that identify known or predicted therapeutic resistance mutations. These features allow Casl3-based therapies to complement therapeutic use.

Developing Therapeutics Cas13-based systems may raise interest in possible non-targeted effects, as pointed out for Cas9. Many uses of Cas9 relate to its ability to edit in DNA that encodes permanent and heritable changes. In contrast, Cas13 has different uses. This is because changes induced by the target RNA and the guide are not heritable. Because Cas13-induced changes are not heritable, Cas13 may be used to regulate, detect, or image RNA molecules inside and outside the cell. This demonstrates its strength as a tool for studying viral diseases.

Applicants develop a set of Cas13 orthologues and corresponding guide RNA sequences that efficiently inhibit replication of two mammalian viruses, lymphocytic choriomeningitis virus (LCMV) and influenza. Applicants will also conduct pilot experiments to test delivery methods for Cas13, screen for non-targeted activities of Cas13, and study viral evolution and guide resistance in response to Cas13 treatment. Applicants have developed improved diagnostic test protocols with shorter turnaround times, design of assays to detect influenza and distinguish between influenza A, B, and C, and lateral flow for instrument-free diagnostics. Develop assays.

The SHERLOCK diagnostic platform has the potential to revolutionize infectious disease testing as a fast, broad-spectrum, field-deployable diagnostic. Evaluation of its technical progress and commercial potential is placed in the context of existing common diagnostic methods (eg, immunoassays and nucleic acid amplification methods). Therefore, during development, its performance metrics (including sensitivity and specificity, time to result, cost per reaction, temperature stability, extrinsic equipment requirements, and ease of use and interpretation) evaluate. Preliminary results suggest that SHERLOCK is comparable to existing FDA-approved pathogen diagnostics.

Five major technical challenges associated with this approach: efficacy of individual guide RNAs, evolution of guide resistance, non-targeted nuclease activity, ease of targeting for influenza replication, and companion Cas13-based therapeutics. Sensitivity.

The first technical challenge is to ensure high efficiency in targeting the viral genome by individual guide RNAs. Unlike messenger RNA, which is made from the genome at a specific rate determined by the strength of the promoter, viral genomes replicate exponentially. To adequately inhibit viral replication, Casl3-mediated cleavage activity must outpace the rate of new viral genome synthesis. Applicants can employ two strategies to mitigate this risk and ensure highly efficient genome cleavage. The two methods are to screen Cas13 orthologs for orthologs with higher nuclease activity and to screen viral genomes for optimal guide sequences. These results may be combined to obtain higher targeting efficiencies. By optimizing the nuclease activity of Cas13 orthologues and selecting optimal guide sequences, Applicants plan to achieve knockdown of viral replication by at least 10-fold. By combining multiple guides simultaneously, Applicants plan to achieve at least a 20-fold knockdown of viral replication.

A second technical challenge is that viruses can develop resistance to targeting guides. This can occur either by direct mutation of the target site or by mutations in other parts of the genome that compensate for the effects of targeted cleavage. RNA viruses are known to have relatively high mutation rates of approximately 10 ⁻⁴ substitutions per base per generation (Sanjuan et al., 2010). Assuming that the guide RNA typically targets a 28-nucleotide region of the viral genome, this means that the probability of one mutation occurring in one target region is approximately 3×10 ⁻³ . Applicants know from previous characterization of Cas13 that two mutations in one target region are required to prevent target cleavage (Abudayyeh et al., 2016). Assuming the two mutations occur independently, the probability of guide resistance occurring in one region is approximately 10 ⁻⁵ . These calculations show the importance of pooling guides. This is because the source of guides further reduces the probability of resistance evolution exponentially (eg, 10 ⁻¹⁰ for 2 guides, 10 ⁻¹⁵ for 3 guides). In addition to accumulating guides, we specifically address this issue by sequencing viral populations before and after treatment with Cas13 to map the evolution of treatment resistance (if any). .

A third technical challenge is the non-targeted nuclease activity by Cas13. Non-targeted nuclease activity is of concern as it can induce side effects in animal models or patients. However, it is important to distinguish the relative effects of non-targeted cleavage by Cas13 and Cas9. Since Cas9 targets DNA, any non-targeted cleavage event will result in a permanent change in the genome of affected cells. However, since Casl3 targets RNA, non-targeted cleavage has only transient effects on gene expression. This is because the half-life of messenger RNA tends to be less than 24 hours (Yang et al., 2003). Despite this contrast between Cas13 and Cas9, Applicants can sequence the transcriptome of cells with and without Cas13 cleavage to measure any non-targeted cleavage activity of Cas13. Specifically, we compare the non-targeting effects of Cas13 guides and siRNAs targeting luciferase transcripts by sequencing. If the non-targeted effects are guide-specific, Applicants will also evaluate the non-targeted effects of the optimal targeted guide. Applicants expect Casl3 to have at least half the non-targeted cleaving activity of siRNA.

A fourth challenge is the ability to target influenza A. Compared to LCMV, influenza A replicates its genome in the nucleus of infected cells, which binds to influenza A protein to form ribonucleoprotein (RNP) (Knipe and Howley, 2007). Prior to proceeding to a comprehensive genome-wide screen, Applicants are able to optimize influenza A targets with several previously published shRNA-derived guides in pilot experiments (Wang et al. Huang et al., 2017; Stoppani et al., 2015; Xu et al., 2015; Wang et al., 2016; McMillen et al., 2016). Specifically, we will optimize the localization of Cas13 (nuclear vs. cytosol) to distinguish whether designing guides targeting positive-sense mRNAs is a more efficient method. can be done. Because this RNA species is released from the RNP, it can be more easily targeted. If these methods do not achieve the desired targeting efficiencies, Applicants will explore the possibility of destabilizing these RNPs by fusing Cas13 to other proteins, as well as methods of altering Cas9 function by making fusion proteins. Yes (Dominguez et al., 2016). Current nucleic acid-targeted strategies against influenza include siRNAs, which have been reported to show 80%-95% knockdown or at least a 5-fold reduction in influenza replication in cell culture models (Huang et al., 2017). ; Xu et al., 2015). Applicants can use one or more guides targeting influenza to increase the reduction of viral replication to the same extent or more, specifically more than 5-fold.

A final technical challenge is the sensitivity of diagnosis with companion Cas13. This is important to ensure that the virus is detected before it spreads to the patient. This is particularly relevant in the context of therapy-resistant mutations. Treatment-resistant mutations are initially low frequency and difficult to detect, but become more detectable at high frequency. However, by the time treatment-resistant mutations become common in patients, damage has already occurred. Higher sensitivity allows for faster detection with rapid Cas13 diagnostics. For these reasons, we have set a very stringent threshold of 50 aM (25 copies per microliter) for influenza diagnosis by Cas13. This threshold is substantially lower than the median influenza A titer in nasal swabs, 10 ⁴ RNA copies per microliter (Ngaosuwankul et al., 2010).

References
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Example 10 Improving Cas13a/C2c2 Diagnostics for Viral Diarrhea Disease

Diarrheal diseases are responsible for more than 500,000 deaths each year, most of them in children in developing countries (Walker CL, Rudan I, Liu L, et al. Global burden of childhood pneumonia and diarrhoea). Global Burden of Diarrhea). Lancet 2013;381:1405-16). Of these diseases, rotavirus is the leading cause of mortality, and other viruses, such as norovirus, have caused severe outbreaks worldwide. These infections are often undiagnosed or misdiagnosed as bacteria and are inappropriately treated with antibiotics, exacerbating patient symptoms and promoting antibiotic resistance. To address this pressing public health challenge, there is a critical need for fast, low-cost, and sensitive tests for the diagnosis of viral diarrheal diseases.

Applicants can use the recently discovered RNA-guided RNA-targeted nuclease Cas13a/C2c2 to create diagnostics for diarrheal disease. Diagnosis is an important first step in patient care. This is because the diagnosis allows the physician to distinguish between bacterial and viral infections, which in turn influences treatment regimens. The CRISPR-Dx platform, called SHERLOCK (Specific High Sensitivity Enzymatic Reporter UnLOCKing), is a highly sensitive and specific nucleic acid detection tool that is portable without relying on the cold chain.

Using viral diarrheal disease as a model, we are able to develop a rapid, field-ready diagnostic method based on the SHERLOCK technology. In many clinical settings, diagnosis of viral disease takes 48 hours or more, even when diagnosis is possible. Several key technical enhancements to SHERLOCK, including reducing the total assay time to 1 hour and changing from a fluorescent readout to a colorimetric output, allow Applicants to perform with a simple heat block. and can be developed into a test that can be visually analyzed by clinicians. This avoids the need to send samples to a centralized testing laboratory, which is expensive, time consuming and can lead to sample degradation. Such delays are particularly important during regional or seasonal disease outbreaks, where rapid public health responses can prevent further spread of emerging infectious agents.

There are about 22 known virus families that infect and cause disease in humans. This number is increasing due to continued population expansion (Woolhouse ME, Howey R, Gaunt E, Reilly L, Chase-Topping M, Savill N. Temporal trends in the discovery of human viruses. ). Proc Biol Sci 2008;275:2111-5). Many of these diseases lack adequate diagnostics, an important first step in treating patients. Current standard diagnostic methods, such as RT-quantitative PCR and ELISA, require specialized equipment, cold chains are time consuming and have high overhead costs. Rapid antigen-based diagnostics have proven difficult to develop. Due to these limitations, there is a great need for fast, inexpensive and highly sensitive diagnostic tools that can be used to detect specific viral pathogens in low-income settings and during pandemics. Applicants are able to develop and improve viral diagnostics for diarrheal disease, one of the leading causes of death in children. The new CRISPR-Cas13a/C2c2 system has the ability to rapidly recognize and cleave specific RNA sequences derived from DNA or RNA (Abudayyeh OO, Gootenberg JS, Konermann S, et al. C2c2 is a single-component A programmable RNA-guided RNA-targeting CRISPR effector (C2c2 is a one-component programmable RNA-guided RNA-targeting CRISPR effector. Science 2016;353:aaf5573), thereby making it an optimal system for viral diagnostics. This system is also particularly suitable for outbreaks. This is because new tests can be designed and deployed in a matter of days.

Given SHERLOCK's high sensitivity and applicability to other infectious diseases, this detection platform is ideal for improving diagnostics in healthcare settings and developing a rapid, field-deployable, multiplexed test for diarrheal viral pathogens. is a good candidate. This approach will improve diagnosis of serious diseases, improve patient care, and reduce inappropriate use of antibiotics.

One of the major limiting factors of existing diagnostic methods is the time lag between patient examination and laboratory results. With viruses such as rotavirus and norovirus, such delay can have lethal effects. In order to speed up the Cas13a/C2c2 detection reaction and develop detection test protocols that do not require nucleic acid extraction, "real-time" diagnostics may be achieved. Applicants are able to turn the time from sample collection to results in less than one hour.

Commonly used nucleic acid detection tests, such as RT-quantitative PCR, require extraction of host material (serum, urine, feces) prior to amplification with PCR inhibitors. This is a significant limitation as extraction is time consuming and requires a skilled technician. Therefore, samples are typically handled in a centralized laboratory and not processed immediately. The isothermal amplification method used in SHERLOCK is not inhibited by host material and the sample preparation test protocol allows direct amplification from urine and faeces for rapid virus detection in the field.

Applicants optimize amplification speed through sequence design and by altering the composition of the detection reaction. Previous studies have shown that isothermal amplification primers have varying performance, and Applicants screen at least 10 primer pairs to identify those with improved performance. Applicants will optimize the guide sequences as well. This is because Casl3a/C2c2 has been shown to have a preference for cleaving specific sequence motifs. Applicants also optimize T7 polymerase concentration, rNTP concentration, background RNA concentration, and magnesium concentration to further increase the speed of detection. Current iterations of the detection reaction typically take 2 hours to achieve sensitive nucleic acid detection, but can be reduced to less than 1 hour and possibly to 30 minutes with optimization.

Development of a colorimetric readout for the detection of viral pathogens

One of the biggest limiting factors for clinical diagnostics is the lack of a robust infrastructure in many clinical settings around the world. Current diagnostic methods often require expensive equipment and highly skilled training, and basic infrastructure such as electricity is a problem for many clinics. By changing the current Cas13a/C2c2 detection from fluorescence output to visual color change, Applicants have developed a user-friendly diagnostic method that can be performed by any medical practitioner without expensive, energy-consuming equipment. can be created.

Applicants have two different methods for colorimetric detection, an enzymatic reporter (eg, lacZ, peroxidase, β-glucuronidase) that produces a colored product from a colorless substrate, and a population of nanoparticles that degrades. A mass of gold nanoparticles bound to single-stranded RNA can be used, which can directly convert nuclease activity into a color change by changing color when the nanoparticles dissolve in solution. Applicants carefully evaluate the performance of these two methods, especially as a readout on the paper surface. This is because speed and ease of color change determination trade off. The best performing methods are tested with clinical samples to further demonstrate their ability to report on the presence of specific nucleic acid sequences.

Development of multiple diagnostics of viral pathogens for diarrheal disease

Viruses that cause diarrhea, including rotavirus, norovirus, Norwalk virus, cytomegalovirus, and viral hepatitis, often go undiagnosed. These viral infections lead to high mortality and morbidity and are often enhanced by drugs such as antibiotics. Applicants have found that determining whether a diarrheal infection is viral can help inform patient treatment, quickly detect viral outbreaks, and reduce unnecessary antibiotic use. Multiple diagnostics can be developed that can

A SHERLOCK is developed for each pathogen using clinical specimens and viral stocks from faeces, urine, and blood. Applicants use multiple sequence alignments to design primer pairs and guides that represent nucleotide diversity within the binding region. Viral RNA undergoes a recombinase polymerase amplification (RPA) reaction. T7 RNA polymerase is added to transcribe the amplified DNA into RNA. Applicants add the resulting RNA to a new reaction mixture consisting of Casl3a, a quenched fluorescent reporter, and a colorimetric system for evaluation.

Example 11 Use of the HUDSON Test Protocol for Virus Detection Directly from Body Fluids

For SHERLOCK to excel in virus detection in any context, it should combine a visual readout with methods that can be detected directly from patient samples. The inventors tested the performance of SHERLOCK in detecting ZIKV and DENV in patient samples and developed HUDSON (Heating Unextracted Diagnostic Samples to Obliterate Nucleases). . This method enables fast and sensitive detection of ZIKV and DENV directly from bodily fluids with a colorimetric readout and was recently demonstrated as part of SHERLOCKv2 (Gootenberg et al. Science doi:10.1126/science.aaq0179; 2018). ). We also designed a SHERLOCK assay to distinguish between multiple viral species and strains to identify clinically relevant mutations.

Detection of ZIKV and DENV in patient samples provides a rigorous test of SHERLOCK sensitivity and viral diversity tolerance. Our ZIKV SHERLOCK assay had a 1 copy (1 cp/μl) sensitivity when tested with the cDNA of the seed stock (Fig. 98). We evaluated the performance of 40 cDNAs derived from samples taken during the 2015-2016 ZIKV outbreak. Of these, 37 were from patient samples with suspected ZIKV infection and 3 were from mosquito sources (Figure 87, Figure 99B, and Table 24). In 16 samples from these patients, SHERLOCK was evaluated by comparing its sensitivity and specificity to other nucleic acid amplification tests, including the commercially available Altona Realstar Zika virus RT-PCR assay (Figures 82C, 88A). 99C, 100, 101, Table 25, also see Discussion). Of the 10 samples that tested positive with the Altona assay, all 10 were detected with SHERLOCK (100% sensitivity). The other 6 samples were negative in both assays (100% specificity, 100% concordance). Our ZIKV assay was free of false positives when tested in healthy urine and water (Fig. 99B). We then demonstrated the ability of SHERLOCK to detect DENV, a related but more diverse flavivirus with symptoms similar to ZIKV infection. All 24 RT-PCR positive DENV RNA samples were confirmed to be DENV positive 1 hour after detection (Figure 99D, Figure 102, Figure 103 and Table 26). SHERLOCK sensitively and specifically detects viral nucleic acids extracted from ZIKV and DENV patient samples.

Although SHERLOCK excels at detecting extracted nucleic acids, the field-deployable rapid diagnostic test does not require an extraction step to detect viral nucleic acids in bodily fluids. Many viruses have been shed in urine or saliva, including ZIKV and DENV, and collection is not invasive (Paz-Bailey et al. N. Engl. J. Med doi:10.1056/NEJMoa1613108 (2017); Andries et al. al. PLoS Negl. Trop. Dis. 9, e0004100 (2015)). To detect viral nucleic acids directly from body fluids by SHERLOCK, we developed a method HUDSON that uses heat and chemical reduction to lyse viral particles and inactivate the high concentrations of RNases observed in body fluids. (Figs. 104A and 89) (Weickmann et al. J. Biol. Chem. 257:8705-8710 (1982)). HUDSON-treated urine or saliva may be added directly to the RPA reaction without dilution or purification without interfering with subsequent amplification or detection (blood products are 1:1 to avoid solidification upon heating). 3). HUDSON and SHERLOCK are capable of sensitive detection of free ZIKV nucleic acid added to urine, whole blood, plasma, serum, or saliva (Figures 83A, 83B, 90A, 105, and 106). Viral nucleic acids are encapsulated within infectious particles, but to mimic clinical infection, we added infectious ZIKV particles to body fluids. When HUDSON was combined with SHERLOCK (Figures 91 and 107), 90 aM (45 cp/μl) in whole blood (Figure 108) or serum (Figure 104B), 0.9 aM (~1 cp/μl) in saliva (Figure 104C), ZIKV RNA from infectious particles could be detected in urine with a sensitivity as high as 20 aM (10 cp/μl). Total turnaround time including fluorescence and colorimetric readout was less than 2 hours (Fig. 104D and Fig. 114). The sensitivities of HUDSON and SHERLOCK range from 1 to 1,000 cp/μl, corresponding to ZIKV RNA concentrations observed in patient samples (Faye et al. J. Clin. Virol. 43:96-101). (2008); Paz-Bailey et al. N. Engl. J. Med. Doi:10.1056/NEJMoa1613108 (2017)). HUDSON in combination with the pan-DENV SHERLOCK assay detected DENV in whole blood, serum and saliva (Figures 109 and 110). DENV was detected directly in 8 of 8 patient serum samples (Figure 104E) and 3 of 3 patient saliva samples tested (Figure 104F). It was detected in saliva in less than 1 hour total turnaround time despite lower virus titers than in serum (Andries et al. PLoS Negl. Trop. Dis. 9, e0004100 (2015)). We detected DENV directly with a colorimetric readout using a horizontal flow strip (Fig. 104G). This demonstrates a HUDSON to SHERLOCK pathway that can detect ZIKV or DENV directly from bodily fluids with minimal equipment.

Because many genetically and antigenically similar flaviviruses co-circulate and have similar symptoms, the inventors developed a diagnostic panel to distinguish between related virus species and serotypes. We identified conserved regions within the ZIKV, DENV, West Nile virus (WNV), and yellow fever virus (YFV) genomes, and analyzed any of the four viruses, and species-specific A flavivirus panel was designed with universal flavivirus RPA primers capable of amplifying the desired crRNA (Fig. 84A). This panel detected synthetic ZIKV, DENV, WNV, and YFV DNA targets with less than 0.22% non-target fluorescence (Fig. 84B, Fig. 92, see also Methods), showing that these four viruses It was confirmed that all pairs of combinations of This demonstrates the ability to detect mimetic co-infections (Figures 84B, 84C, and 93). We also tested DENV serotype 1 at 3.2% non-target fluorescence (FIGS. 84D, 79C, and 94) using DENV-specific RPA primers and serotype-specific crRNAs. A panel was designed that could distinguish ~4 (Fig. 84D). Low levels of non-targeted fluorescence can distinguish serotypes with 100% specificity, offering an alternative to current serotyping methods (Waggoner et al. Microbiol. 51:3418-3420 (2013) ). This DENV panel confirmed the serotypes of 12 RT-PCR serotype patient samples or clinical isolates (FIGS. 84D and 111) and identified 2 clinical isolates as mixed infections. This is a commonly observed phenomenon (Requena-Castro et al. Mem. Inst. Oswaldo Cruz. 112:520-522 (2017)). Thus, SHERLOCK can be extended to distinguish between related viruses or serotypes using a single amplification reaction.

SHERLOCK is uniquely prepared for identification of field-deployable variants. This allows real-time tracking of microbial threats. Genotyping of single nucleotide polymorphisms (SNPs) typically involves PCR and either fluorescence or mass spectrometry detection, requires expensive sample processing, expensive equipment, and has limited field deployability. (Kim et al. Annu. Rev. Biomed. Eng. 9:289-320 (2007). SHERLOCK identifies SNPs by placing synthetic discrepancies close to SNPs in crRNAs, ancestry-specific and Each target can be tested with origin-specific crRNAs (Gootenberg et al. Science 356:438-442 (2017). Three region-specific SNP diagnostics were designed (Figure 112B) and identified these SNPs in synthetic targets, viral seed stocks, and cDNA samples from Honduras, Dominican Republic, and the United States. E) These results demonstrate that SHERLOCK can identify SNPs in samples from ZIKV outbreaks, highlighting the single-nucleotide specificity of SHERLOCK.

It would be of great benefit to rapidly identify emerging drug resistance and other clinically relevant mutations in viruses such as ZIKV and HIV. To rapidly develop a variant identification assay, we used a ZIKV point mutation in the PrM region (S139N) recently associated with fetal microcephaly as a test case (Yuan et al. Science eaam7120 (2017). Within a week of publication (FIGS. 112F and 113), we developed multiple SHERLOCK assays for the S139N mutation (FIGS. 96 and 112G), with visual readouts of 2015-2016 We were able to identify mutations in patient samples from the ZIKV outbreak (Fig. 112H).To further demonstrate the ease of developing a SHERLOCK diagnostic for many clinically relevant mutations, we designed and tested an assay for the six most commonly observed drug resistance mutations in HIV reverse transcriptase in one week (Rhee et al. Nucleic Acids Res. 31:298-303 (2003)) (Figure 97). These examples highlight that SHERLOCK can be used to monitor clinically relevant variants in near real-time.

Combining HUDSON and SHERLOCK, we have created a field-deployable viral diagnostic platform with high performance and minimal equipment or sample handling requirements. This platform has been used in rapid antigen testing (Bosch et al. Sci. Transl. Med 9 (2017), doi:10.1126/scitrtanslmed.aan1589; Balmaseda et al. PNAS USA 114:8384-8389 (2017); Priyamvada et al. PNAS USA 113:7852-7857 (2016)), and is as sensitive and specific as amplification-based nucleic acid diagnostics (Piepenburg et al. PLoS Biol. 4, e204 (2006). )); Yu et al. Angew. Chem. Int. Ed Engl. 56, 992-996 (2017); Eboigbodin et al. Cell 165:1255-1266 (2016); Chotiwan et al. Sci. Transl. Med. 9 (2017) doi:10.1126/scitranslmed.aag0538; Van Ness et al. Furthermore, the method can be readily adapted to detect virtually any virus present in bodily fluids and can be scaled up for multiplexed detection (Gootenberg et al. Science doi:10.1126/ science.aaq0179 (2018)), the reagents may be freeze-dried to avoid recourse to cold chains (Gootenberg et al. Science 356:438-442 (2017)). Detection by Cas13 is a promising next-generation diagnostic method that can be performed almost anywhere in the world, allowing effective rapid diagnosis of viral infections.

material and method

Clinical Specimens/Ethics Statement. The clinical samples used in this study were collected from the Institutional Review Boards/Ethics Review Committees of la Plaza de la Salud (Santo Domingo, Dominican Republic), the Florida Department of Health (Tallahassee, FL), and the Universidad Nacional Autonoma de Honduras (Tegucigalpa, Honduras). ) from clinical studies evaluated and approved in The Institutional Review Board/Ethics Review Committee at the Massachusetts Institute of Technology (MIT) and the Office of Research Subject Projection at the Broad Institute approved the use of samples collected by the institutions indicated above. For dengue virus clinical samples, The Broad Institute Institutional Review Board/Ethics Review Committee approved these samples for use.

Zika virus (ZIKV) clinical samples were collected during the 2015-2016 ZIKV outbreak and analyzed by collaborating institutions using the Hologic Aptima ZIKV assay or published ZIKV RT-PCR or RT-quantitative PCR assays, depending on the collaborating institution. tested on any. Nucleic acid tests and their results are reported in Table 24. RNA extracted from these collected clinical samples was prepared for metagenomic and targeted sequencing, as well as previously published genomes (Metsky et al. Nature 546:411-415 (2017)). cDNA from these 40 preparations was used as input to compare the performance of SHERLOCK and amplicon PCR. RNA extracted from 16 of these samples was tested using the AltonaRealStar Zika virus RT-PCR kit. Details of this assay are provided below. The samples tested and their results are reported in Table 25.

Serum samples from patients confirmed positive for dengue virus (DENV) were surplus from the Broad Institute Viral Genomics Initiative's Comparative Genomics of DENV. Four serum samples and three matched saliva samples of patients confirmed to be DENV positive were also obtained from Boca Biolistics. RNA extracted from DENV RT-PCR positive human serum samples and clinical isolates were in excess of the comparative genomics of DENV from the Broad Institute Viral Genomics Initiative. Clinical isolates were prepared by incubating human serum on C6/36 cells and harvesting RNA from cell supernatants according to the RNA extraction protocol outlined below.

Production of LwCasl3a and crRNA LwCasl3a was purified in-house (Gootenberg et al. Science 356:438-442 (2017)) or by Genscript. The crRNA DNA template was annealed to the T7 promoter oligonucleotide at a final concentration of 10 μM in 1×Taq reaction buffer (NEB). This involved denaturation at 95°C for 5 minutes followed by annealing down to 4°C at 5°C for 1 minute. The crRNA was transcribed in vitro using the HiScribe T7 High Yield RNA Synthesis Kit (NEB). Transcriptions were performed in volumes scaled up to 30 μl according to the manufacturer's instructions for short RNA transcripts. Reactions were incubated overnight at 37°C. Transcripts were purified using RNAClean XP beads (Beckman Coulter) at a ratio of 2x reaction volume supplemented with an additional 1.8x isopropyl alcohol. Some crRNAs were synthesized by Integrated DNA Technologies (IDT).

Sample preparation. Viral RNA was extracted from 140 μl of input material using the QIAamp Viral RNA mini kit with carrier RNA (QIAGEN) according to the manufacturer's instructions. Samples were eluted with 60 μl of nuclease-free water and stored at −80° C. until use.

For cDNA generation, 5 μl of extracted RNA was converted to single-stranded cDNA using a previously published method (Matranga et al. Genome Biol. 15:519 (2014)). Briefly, RNA was reverse transcribed with SuperScript III (Invitrogen) and random hexamer primers. The RNA-DNA duplex was then digested with RNase H. The cDNA was stored at -20°C until use. In some experiments (Fig. 99C and Fig. 100), RNase H treatment was not performed and reverse transcription was performed using SuperScript IV at 55°C for 20 minutes.

One cultured isolate ZIKV pernambuco (isolate PE243, KX197192.1) was used in ZIKV detection experiments as a positive control or ancestral sequence control. Viral RNA was extracted from 140 μl seed stock samples using the RNA extraction method described above.

RNase inactivation of urine samples was performed by addition of TCEP/EDTA and heating of the samples. TCEP and EDTA were added to urine samples at final concentrations of 100 mM and 1 mM, respectively. Two test protocols were used: one step inactivation at 95°C for 10 minutes, or two steps inactivation at 50°C for 20 minutes followed by 95°C for 5 minutes. Inactivation was performed using a thermal cycler or dry heat block.

RNase inactivation of Zika virus in whole blood, plasma, serum, and saliva samples was performed by addition of TCEP/EDTA and heating of the samples. TCEP and EDTA were added to urine samples at final concentrations of 100 mM and 1 mM, respectively. A two-step inactivation was used of 5 min at 50° C., then 5 min at 64° C. (blood products or saliva) or 20 min at 50° C., then 5 min at 95° C. (urine). Inactivation was performed using a thermal cycler or dry heat block.

RNase inactivation of DENV in whole blood, serum, and saliva samples was performed by addition of TCEP/EDTA and heating of the samples. TCEP and EDTA were added to urine samples at final concentrations of 100 mM and 1 mM, respectively. Two steps of inactivation were used at 42°C (or 37°C depending on the experiment) for 20 minutes, followed by 64°C for 5 minutes. Inactivation was performed using a thermal cycler.

RPA reactions and primer design. The Twist-Dx RT-RPA kit was used in the RPA reactions according to the manufacturer's instructions. Primer concentration was 480 nM. Amplification reactions involving RNA used Murine RNase inhibitor (NEB M3014L) at a final concentration of 2 units per microliter. All RPA reactions were 20 minutes unless otherwise stated.

ZIKV detection used RPA primers RP819/RP821 from a recent publication (Gootenberg et al. Science 356:438-442 (2017)). Universal DENV detection uses an equal mixture of the published RPA primers DENV1-3-RPA-RP4/DENV1-3-RPA-FP13 and DENV4-RPA-RP2/DENV4-RPA-FP3, regardless of serotype. (Abd El Wahed et al. PLoS One 10, e0129682 (2015)). The flavivirus panel used the RPA primers FLAVI-NS5fwd-1/FLAVI-NS5rev-1. For the serotype-discriminating DENV panel, the RPA primers DENV-3UTRfwd-1/DENV-3UTRrev-1 were used. For region-specific Zika SNP detection, RPA primers DOMUSA-5249-fwd/DOMUSA-5249-rev (DOMUSA5249 SNP), USA-935-fwd/USA-935-rev (USA935 SNP), and HND-2788-fwd /HND-2788-rev (HND2788 SNP) was used. Detection of the Zika SNP associated with microcephaly used the RPA primers ZIKV-mcep-fwd and ZIKV-mcep-rev. For detection of HIV reverse transcriptase drug resistance SNPs, RPA primers HIVRT-149F/HIVRT-348R (K65R, K103N, and V106M SNPs) and HIV-462F/HIVRT-601R (Y181C, M184V, and G190A SNPs) were used. board. See Table 28 for a complete list of RPA primer names and sequences.

Design of Cas13 detection reactions and crRNAs. Detection reactions were performed as described above, except that the background RNA input per reaction was reduced from 100 ng to 0-25 ng (Gootenberg et al. Science 356:438-442 (2017)). This can speed up the reaction without introducing any spurious cleavage of the reporter oligonucleotide. RNase Alert v2 (Thermo) was used as a reporter unless otherwise stated. A Biotek microplate reader (Synergy H4, Neo2, and Cytation 5) was used to measure the fluorescence of the detection reactions. Fluorescence kinetics were monitored using a monochromator with 485 nm excitation, 520 nm emission and readings every 5 minutes for up to 3 hours. No significant difference in sensitivity between different machines was found. Therefore, these machines were used interchangeably. Fluorescence values reported are background subtracted or template specific values. Time points reported are listed in the figure notes.

For ZIKV detection, we used the crRNA “Zika target crRNA2” from a recent publication (Gootenberg et al. Science 356:438-442 (2017)). Universal DENV detection used an equal mixture of three crRNAs and D1-3UTrat10660, D2/3-3UTrat10635, D4-3UTrat10620 regardless of serotype. The flavivirus panel used crRNAs ZIKV-NS5at9227 (ZIKV), DENV-NS5at9127 (DENV), WNV-NS5at9243 (WNV), and YFV-NS5at9122 (YFV). A serotype-discriminating DENV panel used crRNAs D1-3UTRat10457 (DENV1), D2-3UTrat10433 (DENV2), D3-3UTrat10419 (DENV3), and D4-3UTrat10366 (DENV4). For region-specific Zika SNP detection, crRNA DOMUSA-5249-ancestor/DOMUSA-5249-derived (DOMUSA5249 SNP), USA-935-ancestor/USA-935-derived (USA935 SNP), and HND-2788-ancestor/HND -2788 origin (HND2788 SNP) was used. For detection of the Zika SNP associated with microcephaly, crRNA ZIKV-mcep-snp3syn5-ancestor/ZIKV-mcep-snp3syn5-derived (design shown in FIG. 112F) and crRNA ZIKV-mcep-snp7-ancestor/ZIKV- The mcep-snp7-derived (design shown in Figure 105) was used. For the detection of drug resistance SNPs in HIV reverse transcriptase, crRNA HIVRT-K65R-ancestor/HIVRT-K65R-derived (K65R SNP), HIVRT-K103N-ancestor/HIVRT-K103N-derived (K103N SNP), HIVRT-V016M-ancestor/ HIVRT-V106M-derived (V106M SNP), HIVRT-Y181C-ancestor/HIVRT-Y181C-derived (Y181C SNP), HIVRT-M184V-ancestor/HIVRT-M184V-derived (M184V SNP), and HIVRT-G190A-ancestor/HIVRT-G190A-derived (G190A SNP) was used. See Table 29 for a complete list of crRNA names and spacer sequences. See Discussion for further discussion of the effect of crRNA sequence and secondary structure on activity.

Sidestream detection reaction. Sidestream detection was achieved with commercially available detection strips (Milenia Hybridect 1, TwistDx, Cambridge, UK) using a custom probe oligonucleotide (LF-polyU, see Table 30 for sequence). The Cas13 detection reaction was diluted 1:5 in Hybridect assay buffer and the strips were submerged and incubated for 5 minutes at room temperature. The strip was then removed and photographed using a smart phone camera.

RT-PCR experiments. RT-PCR for ZIKV detection was performed using the AltonaRealStar Zika virus RT-PCR kit (RUO version) according to the manufacturer's specifications on a Lightcycler 96 RT-PCR machine (Roche). 10 μl of ZIKV RNA extracted from patient samples was used as input for RT-PCR. 1 μl of internal control (IC) was used for each sample.

data analysis. After 0 minutes (FIGS. 98, 99D, 102, 103), 10 minutes (FIGS. 84, 99B-99C, and 104) or 20 minutes (FIG. 112) after minimal fluorescence was observed. Background was subtracted by subtracting fluorescence values. For both flavivirus and DENV panels, background-noise-removed fluorescence was normalized to target-specific fluorescence. Target-specific fluorescence is the background-subtracted mean fluorescence of no input (water) controls with the same crRNA subtracted from the background-subtracted fluorescence of a given DNA target with a given crRNA at each time point. be.

From the analysis of ZIKV samples from the 2015-2016 outbreak (Figure 99B), a threshold was used to determine the presence or absence of ZIKV. Background-noise subtracted fluorescence from five negative control samples, four healthy human urine samples from one donor and one no-input water control, was used to determine the ZIKV SHERLOCK fluorescence threshold. That is, for each of these five samples, we took the mean m _s and standard deviation σ _s of fluorescence over three technically identical samples. The threshold was set as the center value of {m _s +3σ _s } of 5 values. In FIG. 1C, the same calculation {m _s +3σ _s } was performed with one no-input control to determine the threshold. Information from the genome assembly was used to determine a threshold amplicon PCR yield. First, the amplicon PCR yield for each sample was calculated by taking the lowest concentration from each of the two amplicon PCR sources (Figure 87A). The objective is then to determine the yield that best predicts whether a particular target portion r of the genome is present in the sample (in this case the RPA amplification product that we detect with SHERLOCK). is. The probability Pr _s (r) that a particular target portion r is present in sample s may be estimated as the fraction of the ZIKV genome sequenced and assembled from the cDNA of sample s (the calculation of the probability across the genome is It is preferable to simply check whether there is genomic coverage at portion r, as lack of coverage does not necessarily indicate the absence of a particular target portion r). Data for this analysis are derived from individual technically identical samples from a recent genome sequencing study of the ZIKV outbreak (Metsky et al. Nature 546:411-415 (2017)). A plot of the amplification product PCR yield versus the fraction of genome covered is shown in FIG. 88B. The value Pr _s (r) may be used to estimate accuracy and recall for threshold selection. In particular, an estimate of the number of samples without a particular target moiety r is the sum of Pr _s (r) for all samples. Similarly, among the samples P whose amplification product PCR yield exceeds a predetermined threshold, the number of correctly labeled r as present is estimated as the sum of Pr _s (r) in the samples P. FIG. 87C shows precision and recall for each choice of threshold and F _0.5 score. The F _0.5 score is a composite metric that considers the threshold ability to correctly classify samples with the target portion of ZIKV. The amplicon PCR yield threshold is set to maximize the F _0.5 score. See Discussion for further discussion of the sensitivity and specificity of SHERLOCK compared to amplicon PCR and other methods.

The ZIKV assay was used to calculate the fluorescence threshold of DENV SHERLOCK as described above. Thresholds were determined using background-subtracted fluorescence from eight no-input negative controls. For each of these 8 no-input controls s, we took the mean m _s and standard deviation σ _s of the fluorescence intensity across the 3 technically identical samples and set the threshold to 8 values was set to the center value of {m _s +3σ _s } of .

For multivirus or serotype panels, the non-target fluorescence of each target was calculated relative to the other crRNAs in the panel. This compares the observed target-specific fluorescence intensity with the corresponding target:crRNA pairs at 3 hours post-detection (when maximal fluorescence was observed, or when the signal was saturated). This was done by calculating the percentage of fluorescence specific to the paired targets. Non-target fluorescence reported in the literature was the largest observed for the four targets in a given panel.

For SNP identification, background-noise-removed fluorescence values were calculated using ancestral target crRNA and derived target crRNA. We determined the presence or absence of SNPs by taking the ratio of ancestral background-subtracted fluorescence to ancestral background-subtracted fluorescence. A SNP identification index was calculated for the HIV SNPs (Figure 106). This index is a ratio obtained by dividing the fluorescence intensity ratio of the origin allele by the fluorescence intensity ratio of the ancestral allele. The SNP identification index is equal to 1 if there is no characteristic force between the two alleles, and is higher when the ratio of fluorescence intensities of the two alleles is different. See "Discussion" for further discussion of factors that affect the distinguishability of individual SNPs using SHERLOCK.

ZIKV and DENV detection experiments. PE243 (MF352141.1) seed stock cDNA was used at a stock concentration of 6.8×10 ⁴ cp/μl. cDNA was serially diluted 1:10 in ultrapure water (Life Technologies) or healthy urine (Lee Biosolutions). 4-8 μl of each sample was inactivated and 1-2 μl was used as input for the RPA reaction. RNA from PE243 seed stock was used at 2.72×10 ⁵ cp/μl. The virus was originally isolated from a febrile patient with a rash on May 13, 2015, and was tested in Vero cells at the FIOCRUZ Pernambuco Institute (E. Marques) in Brazil and the MIT Gehrke Institute in 2016. generation has taken place. PE243 is one of the first isolates from the Zika outbreak in Brazil (Donald et al. PLoS Negl. Trop. Dis. 10, e0005048 (2016). Serially diluted 1:10 in healthy urine (Lee Biosolutions) 4-8 μl of each sample was inactivated and 1-2 μl was used as input for RPA reactions 14 mM MgAc for DENV detection, 17 mM for ZIKV detection of MgAc was used.

Culture isolate ZIKV strain PRVABC59 (KU501215) from Puerto Rico (Donald et al. PLoS Negl. Trop. Dis. 10, e0005048 (2016); Lanciotti et al. Emerg. Infect. Dis. 22:933-935 (2016) ) was obtained from the US BEI repository as cat number ATCC VR-1843 and was used to spike virus into healthy urine, saliva, whole blood, and serum samples. PRVABC59 was cultured in insect and non-human primate cell lines, and HuH-7 human hepatoma cells were used to drive infectious particles in virus stocks as described above (Lambeth et al. J. Clin. Microbiol. 43 :3267-3272 (2005).To dilute the virus in healthy saliva (Lee Biosolutions), whole blood (Research Blood Components), and serum (Millipore Sigma), culture isolate DENV2 strain New Guinea C (NGC) was used. Using.

Virus panel experiments. To account for the sequence diversity of four different viruses of the flavivirus family (ZIKV, DENV, WNV, and YFV), we used the CATCH method (Compact Aggregation of Targets for Comprehensive Hybridization). target small agglutination) was applied to search for conserved regions suitable for the universal flavivirus RPA primer pair. An implementation of this method is available on GitHub under the MIT license (https://github.com/broadinstitute/catch). This method allowed us to narrow our search for primer pairs within the conserved regions of NS5.

Initial testing of the flavivirus and DENV panels used synthetically generated DNA templates as input at a concentration of 10 ⁴ copies/μl. No input (water) controls were used as negative controls for each of the crRNAs tested. Three technically identical samples were used in all panel experiments. For all flavivirus panel experiments, the MgAc concentration of the RPA reactions was 20 mM, and for all DENV panel experiments, the MgAc concentration of the RPA reactions was 14 mM.

Initial testing of the flavivirus panel generated ZIKV template sequences from (KX197192), DENV (NC_001477.1), WNV (NC_09942.1), and YFV (AY968065.1). A part of NS5 is amplified by RPA reaction against these flaviviruses.

Initial testing of the DENV panel generated DENV1 synthetic template sequences from (KM204119.1), DENV2 (KM204118.1), DENV3 (KU050695.1), DENV4 (JQ822247.1). A portion of the 3' untranslated region of DENV1-4 is amplified by the RPA reaction. This DENV panel was additionally tested against RNA extracted from clinical samples and seed stocks.

SNP identification test. Identification of region-specific SNPs validated the performance of the SNP identification assay using a synthetic template containing a 400nt fragment of the ZIKV genome with ancestral or derived alleles. ZIKV cDNA samples from three countries (USA, Honduras, and Dominican Republic) were also used to confirm performance against mosquito sources and clinical samples. See Table 24 for additional information regarding these cDNA samples. The PE243 seed stock cDNA (KX197192.1) was used as an outgroup control at 300 cp/μl. A no input (water) control was also used. In SNP identification experiments associated with microcephaly, a synthetic template containing a 400 nt fragment of the ZIKV genome with an ancestral or derived allele was used at 10 ⁴ cp/μl and cDNA from PE243 seed stock was used at 300 cp/μl. board. For HIV drug resistance SNP identification experiments, synthetic templates containing 468 nt fragments of the HIV genome with ancestral or derived alleles were used at 10 ⁴ cp/μl. See Table 30 for a complete list of synthetic template names and sequences. Three technically identical samples were used in all SNP identification experiments.

consideration

Discussion of the sensitivity and specificity of SHERLOCK in ZIKV detection. The inventors have shown that SHERLOCK is a highly sensitive and specific nucleic acid detection method. ZIKV detection was the primary test for the sensitivity of SHERLOCK. Mainly because detection of ZIKV is very difficult due to low viral titers and sample degradation (Paz-Bailey et al. N. Engl. J. Med. Doi:10.1056NEJMoa1613108 (2017)). . We tested a set of samples (37 suspected positive patient samples and 3 mosquito sources) from the 2015-16 ZIKV outbreak by both SHERLOCK and amplification product PCR. to determine the presence or absence of ZIKV nucleic acid in a given sample. On 16 samples from these patients we compared SHERLOCK to two FDA-EUA-approved ZIKV diagnostics: 1) Hologic Aptima ZIKV assay and 2) AltonaRealStar Zika virus RT-PCR assay.

To compare the SHERLOCK and AltonaRealStar Zika virus RT-PCR assays, we compared both assays on a set of 16 patient samples. Two assays were performed with identical reverse transcription conditions and input volumes (20 min reverse transcription and 10 μl input). Reverse transcription reaction conditions dilute cDNA 1:4 from RNA input. Therefore, the amount of RNA we use for SHERLOCK is ¼ of the amount used in the Altona kit. We observed that these two methods are equally sensitive. Ten of the 16 samples were positive by each method, with an overall concordance of 100% (Fig. 99C and Fig. 100).

We then compared the SHERLOCK and Altona assays to the Hologic Aptima Zika virus assay. The Hologic Aptima Zika virus assay uses a larger input volume (greater than 500 μl). All 10 samples that tested positive in both the Altona assay and SHERLOCK were positive in the Hologic assay (Table 25). Three samples were positive in the Hologic assay, but not in the other two assays. This is likely due to the sample input volume of the Hologic assay being more than 50 times larger. Thus, SHERLOCK is as sensitive as the RT-PCR assay for ZIKV detection, and its sensitivity for the Hologic assay is limited to the input volume.

The rationale for including amplicon PCR data was based on our observations when performing broad-scale genome sequencing during the ZIKV outbreak, when partial genomes were very common. (Metsky et al. Nature 546:411-415 (2017)). This suggests that the genome-wide comparison standard offers greater sensitivity than single amplicon methods (eg RT-PCR). For the amplicon PCR method, we quantified the amplificate PCR products using an Agilent tapestation and chose a threshold of 2 ng/μl to determine the presence or absence of ZIKV. This threshold maximizes accuracy as measured by the genomic sequence coverage of the amplicon PCR products (Fig. 100, see Methods for details). Despite the different regions of the ZIKV genome targeted by these two methods, both showed high concordance (82.5%) (Fig. 84C and Figs. 88A-88C). The amplicon PCR method tiles the entire ZIKV genome, but SHERLOCK uses only one amplicon with a length of 128 nt, which is shorter than the 300-400 nt PCR amplicon (Fig. 101). Therefore, highly degraded samples (with short RNA fragments) may be detected more easily by SHERLOCK than by amplicon PCR. Conversely, if the SHERLOCK amplicon itself is degraded but not the rest of the genome, amplicon PCR will detect the remaining portion of the genome present in the sample.

This sensitivity of SHERLOCK is combined with high specificity. We have demonstrated SNP sensitivity, serotyping, and species-level specificity using various SHERLOCK assays. We also tested a number of negative controls, including healthy body fluids, water, and possibly nucleic acids from other viruses. Based on these results, we do not expect to observe many false positives (if any) with SHERLOCK.

Sources of variability in SHERLOCK performance. As discussed in the SHERLOCK original paper supplement, RPA performance is highly variable and dependent on template sequence, amplicon length, and other factors (Gootenberg et al. Science 356:438-442 (2017)). ). The Cas13 detection step amplifies the fluorescence signal from 100-fold to over 1,000-fold depending on the input concentration of the RPA amplification product. As a result, unless the diversity is very large, SHERLOCK is fairly robust to diversity in either RPA amplification or Casl3 detection.

To design a multiviral and multiserotype panel, we used degenerate RPA primers to capture the remarkable sequence diversity of the RNA viruses of interest. In some cases, primer degeneracy can vary amplification efficiency for different targets. Generally, this can be managed by optimizing the RPA reaction (such as adjusting primer and magnesium concentrations).

In addition to RPA diversity, we observed some diversity in the Cas13 detection step of SHERLOCK due to the effects of spacer GC content, poly-U stretches, and secondary structure on crRNA performance. Some crRNAs are more active than others, and some crRNAs are more active in the absence of target (ie, no input control). We also observed that some crRNAs were less pure than others after in vitro transcription. However, after purification, almost all crRNAs become highly active (with a few exceptions due to undesirable secondary structure of the spacer, such as when most of the spacer can pair with itself).

The low fluorescence of ZIKV in the flavivirus panel (Fig. 84B) may be due to a combination of the above factors (as well as other crRNAs used in this study).

Factors affecting SNP discrimination by SHERLOCK. Different spacer RNA sequences were observed to have different levels of performance in the SHERLOCK detection step. Although the factors leading to these performance differences have been discussed, there are also implications related to SNP detection.

SNP detection relies on a pair of crRNAs that differ from the target sequence by one or two nucleotides and thus have different activities towards the target molecule in a sequence-dependent manner. SNP discrimination is successful when the presence of a second mismatch between crRNA and target RNA leads to observable differences in secondary cleavage. Therefore, the following may limit the success of SNP identification.
• One additional discrepancy in highly active crRNAs, which may not reduce activity sufficiently for strong discrimination, was observed with several crRNAs. Possible solutions include 1) diluting the RPA product before adding it to the detection reaction or 2) using low crRNA concentrations.
• If one allele is preferentially amplified over other alleles during RPA (due to changes in template secondary structure), this may bias the output of SHERLOCK. The inventors have not observed this, but it is a possibility.
• Due to labile pairing of RNA, some crRNAs may bind weakly in the absence of Watson-Crick base pairing. This was observed with some of our A>G or G>A mutations (eg USA935). The "U" of crRNA can be attached to either the original or ancestral nucleotide. However, even in this scenario it is easy to distinguish between the two alleles. This is because the G-targeted crRNA contains a C nucleotide that does not pair with A.

Given these limitations, crRNAs with low activity (which can be achieved by shortening the spacer) are more suitable for SNP detection, and unstable base pairing may affect the signal of SHERLOCK. but does not completely invalidate SNP identification.
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Various modifications and variations of the above-described methods, pharmaceutical compositions, and kits of this invention will be apparent to those skilled in the art without departing from the scope and spirit of this invention. Although the invention has been described in connection with specific embodiments, it is obvious that further modifications are possible and that the invention is unduly limited to such specific embodiments as claimed. isn't it. Indeed, various modifications of the above-described modes for carrying out the invention which are obvious to those skilled in the art are intended to be within the scope of the present invention. This application is generally intended to cover any variations, uses, or adaptations of the invention in accordance with its principles and within common practice known in the art to which the invention pertains. , including such departures from the present disclosure applicable to the principal features set forth herein above.

Claims (44)

a CRISPR system comprising an effector protein and one or more guide RNAs designed to bind to the corresponding target molecule; and an RNA-based masking construct,
A nucleic acid detection system, wherein said target molecule comprises one or more viral target molecules. a CRISPR system comprising an effector protein and one or more guide RNAs designed to bind to the trigger RNA;
A polypeptide detection system comprising an RNA-based masking construct; and one or more detection aptamers comprising a masked RNA polymerase promoter binding site or a masked primer binding site. A method of detecting a virus in a sample, comprising:
dispensing a sample or set of samples into one or more discrete volumes containing the CRISPR system of claim 1 or 2;
incubating the sample or set of samples under conditions sufficient to allow the one or more guide RNAs to bind to the one or more target molecules;
activating said CRISPR effector protein by binding said one or more guide RNAs to said one or more target molecules, wherein activation of said CRISPR effector protein produces a detectable positive signal; said RNA-based masking construct is modified such that said virus is present in said sample; and detecting said detectable positive signal, wherein detecting said detectable positive signal is the presence of one or more viruses in said sample method). 4. The method of claim 3, wherein said sample comprises two or more viruses and said method distinguishes between said two or more viruses. 5. The method of claim 3 or 4, wherein said guide RNA detects single nucleotide variants of said one or more viruses. 6. The method of claim 5, wherein said guide RNA further comprises one or more synthetic mismatches. 6. The method according to any one of claims 3 to 5, wherein the one or more CRISPR-based guide RNAs each comprise a set of universal viral guide RNAs that detect viruses and/or virus strains in a set of viruses. described method. 8. The method of claim 7, wherein said guide RNA is generated using a population coverage method. A method of detecting a virus, comprising:
exposing the CRISPR system of any one of claims 1 or 2 to a sample;
activating an RNA effector protein such that binding of said one or more guide RNAs to said one or more microorganism-specific target RNAs or one or more trigger RNAs produces a detectable positive signal; and detecting said detectable positive signal, wherein detection of said detectable positive signal indicates the presence of one or more viruses in said sample. 10. The method of claim 9, wherein the CRISPR system is on the surface of a substrate and the substrate is exposed to the sample. 11. The method of claim 10, wherein the same or different CRISPR systems are applied to multiple discrete locations on the substrate. 12. The method of claim 11, wherein the same or different CRISPR systems are applied to multiple discrete locations on the substrate. A method according to any of claims 10-12, wherein said substrate is a substrate of flexible material. 14. The method of claim 13, wherein the flexible material substrate is a paper substrate, a cloth substrate, or a flexible polymer substrate. 13. The method of claim 12, wherein the different CRISPR systems detect different microorganisms at respective locations. 4. The substrate is passively exposed to the sample by temporarily immersing the substrate in a fluid to be collected, applying a fluid to be tested to the substrate, or contacting a surface to be tested with the substrate. 13. The method according to 13. 17. The method of claim 16, wherein said sample is a biological or environmental sample. Said environmental samples include food samples, beverage samples, paper surfaces, cloth surfaces, metal surfaces, wood surfaces, plastic surfaces, soil samples, fresh water samples, waste water samples, saline samples, air or other gases. 18. The method of claim 17 obtained from sample exposure, or a combination thereof. The biological sample may be a tissue sample, saliva, blood, plasma, serum, feces, urine, saliva, mucus, lymph, synovial fluid, cerebrospinal fluid, ascites, pleural effusion, seroma, pus, or swab of skin or mucosal surface. 18. The method of claim 17, obtained from 20. Any one of claims 17-19, wherein said environmental or biological sample is a raw sample and/or said one or more target molecules have not been purified or amplified from said sample prior to applying said method. The method described in the section. A method of monitoring viral disease outbreaks and/or progression, comprising:
exposing the CRISPR system of claim 1 or 2 to a sample;
activating RNA effector proteins by binding said one or more guide RNAs to said one or more target sequences containing non-synonymous viral mutations such that a detectable positive signal is produced; and said detectable detecting a positive signal, wherein detection of said detectable positive signal is indicative of the type of virus strain present in said sample. exposing the CRISPR system comprises placing one or more CRISPR systems in one or more discrete volumes and adding a sample or portion of a sample to the one or more discrete volumes; 22. The method of claim 21. A method of screening a sample for viral antigens and/or virus-specific antibodies, comprising:
exposing the CRISPR system of claim 2 to a sample, wherein said one or more aptamers bind to one or more viral antigens or one or more virus-specific antibodies, and wherein said aptamers bind to said one or more encodes a barcode that identifies the one or more viral antigens or one or more virus-specific antibodies to which the above aptamers bind, and the guide RNA is designed to detect the barcode) ;
binding of said one or more guide RNAs to said one or more microorganism-specific target RNAs or one or more trigger RNAs activates said RNA effector proteins such that a detectable positive signal is produced; and detecting said detectable positive signal, wherein said detectable positive signal comprises one or more viral antigens or one or more virus-specific antibodies in said sample. present). A method according to any one of claims 3 to 23, wherein said virus is a DNA virus. The DNA viruses include Myoviridae, Podoviridae, Siphoviridae, Alloherpesviridae, Herpesviridae (including human herpesvirus and varicella-zoster virus), Marocoherpesviridae, Lipothrixviridae, Rudivirus. Adenoviridae, Amplaviridae, Ascoviridae, Asphaviridae (including African swine fever virus), Baculoviridae, Cicaudaviridae, Clavaviridae, Corticoviridae ( Corticoviridae), Fuseroviridae, Globroviridae, Guttaviridae, Humanrosaviridae, Iridoviridae, Maseilleviridae, Mimiviridae, Nudiviridae, Nimaviridae, Pandoraviridae, Papillomaviruses family, Phycodnaviridae, Plasviridae, Polidnaviridae, Polyomaviridae (including Simianvirus 40, JC virus, BK virus), Poxviridae (including cowpox and smallpox), Sphaerolipovirus 25. The virus of claim 24, which is of the Sphaerolipoviridae, Tectiviridae, Turriviridae, Dinodnavirus, Salterprovirus, Rhizidovirus, or combinations thereof. Method. 24. The method of any one of claims 3-23, wherein said viral infection is caused by a double-stranded RNA virus, a positive-stranded RNA virus, a negative-stranded RNA virus, a retrovirus, or a combination thereof. Said viruses are Coronaviridae, Picornaviridae, Caliciviridae, Flaviviridae, Togaviridae, Bornaviridae, Filoviridae, Paramyxoviridae, Pneumoviridae, Rhabdoviridae , Arenaviridae, Bunyaviridae, Orthomyxoviridae, or Deltavirus. Said viruses are coronavirus, SARS, poliovirus, rhinovirus, hepatitis A, Norwalk virus, yellow fever virus, West Nile virus, hepatitis C virus, dengue virus, Zika virus, rubella virus, Ross River virus, Sindbis Viruses, Chikungunya virus, Borna virus, Ebola virus, Marble virus, Measles virus, Mumps virus, Nipah virus, Hendra virus, Newcastle disease virus, Human respiratory syncytial virus, Rabies virus, Lassa virus, Hantavirus, Crimea virus 27. The method of claim 26, which is Congo hemorrhagic fever virus, influenza, or hepatitis D virus. A method of detecting one or more microorganisms in a sample, comprising:
A method comprising contacting a sample with a nucleic acid detection system according to any of claims 1 or 2; and subjecting said contacted sample to a lateral flow immunochromatographic assay. Said nucleic acid detection system comprises an RNA-based masking construct comprising a first molecule and a second molecule, said lateral flow immunochromatographic assay preferably detecting said first molecule at discrete detection sites on the horizontal flow strip surface. and detecting the second molecule. 3. The first molecule and the second molecule are detected by binding to an antibody that recognizes the first or second molecule and detecting the bound molecule, preferably with a sandwich antibody. 30. The method according to 30. said horizontal flow strip comprising an upstream first antibody directed against said first molecule and a downstream second antibody directed against said second molecule, wherein said target nucleic acid is present in said sample; Otherwise, the uncleaved RNA-based masking construct binds to the first antibody, and if the target nucleic acid is present in the sample, the cleaved RNA-based masking construct binds to the first antibody and the second antibody. 32. The method of claim 30 or 31, which binds both antibodies. A method of detecting a virus, comprising:
obtaining a sample from a subject, wherein said sample is urine, serum, blood, or saliva;
amplifying the sample RNA;
mixing said sample with an effector protein, one or more guide RNAs designed to bind to a corresponding virus-specific target molecule, and an RNA-based masking construct;
activating said RNA effector protein by binding said one or more guide RNAs to said one or more virus-specific target molecules, wherein activation of said CRISPR effector protein is detectable said RNA-based masking construct is modified such that a positive signal is produced); and detecting said signal, wherein said detection of said signal indicates said virus is present;
A method, wherein the method does not include the step of extracting RNA from the sample. 34. The method of claim 33, wherein said amplifying step is of duration selected from the group consisting of 2 hours, 1 hour, 30 minutes, 20 minutes, and 10 minutes. 34. The method of claim 33, wherein said detection step is of duration selected from the group consisting of 3 hours, 2 hours, 1 hour, 30 minutes, 20 minutes, and 10 minutes. 34. The method of claim 33, wherein the volume of sample required for detection is between 100 μl and 1 μl. 34. The method of claim 33, wherein said virus is Zika virus. 34. The method of claim 33, wherein said sample contains two or more viruses, and wherein said two or more viruses are distinguished. 34. The method of claim 33, wherein said RNA-based masking construct comprises an RNA oligonucleotide to which a detectable ligand and masking moiety are attached. 34. The method of claim 33, wherein said method further comprises a nuclease inactivation step and a virus inactivation step prior to amplifying said sample RNA. 41. The method of claim 40, wherein said nuclease inactivation step is performed at a temperature in the range of 37°C to 50°C. 41. The method of claim 40, wherein said nuclease inactivation step is of duration selected from 5 minutes, 10 minutes, 15 minutes and 20 minutes. 41. The method of claim 40, wherein said viral inactivation step is performed at a temperature in the range of 64°C to 95°C. 41. The method of claim 40, wherein said virus inactivation step is 5 minutes.

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